icml_2018.json

[{"Sound Abstraction and Decomposition of Probabilistic Programs": ["Steven Holtzen", "Guy Van den Broeck", "Todd Millstein"], "Graphical Nonconvex Optimization via an Adaptive Convex Relaxation": ["Qiang Sun", "Kean Ming Tan", "Han Liu", "Tong Zhang"], "Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow": ["Xiao Zhang", "Simon Du", "Quanquan Gu"], "Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms": ["Yi Wu", "Siddharth Srivastava", "Nicholas Hay", "Simon Du", "Stuart Russell"], "Active Learning with Logged Data": ["Songbai Yan", "Kamalika Chaudhuri", "Tara Javidi"], "Kernel Recursive ABC: Point Estimation with Intractable Likelihood": ["Takafumi Kajihara", "Motonobu Kanagawa", "Keisuke Yamazaki", "Kenji Fukumizu"], "Adafactor: Adaptive Learning Rates with Sublinear Memory Cost": ["Noam Shazeer", "Mitchell Stern"], "Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks": ["Lechao Xiao", "Yasaman Bahri", "Jascha Sohl-Dickstein", "Samuel Schoenholz", "Jeffrey Pennington"], "Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation": ["Hugo Raguet", "loic landrieu"], "On Acceleration with Noise-Corrupted Gradients": ["Michael Cohen", "Jelena Diakonikolas", "Orecchia Lorenzo"], "Comparing Dynamics: Deep Neural Networks versus Glassy Systems": ["Marco Baity-Jesi", "Levent Sagun", "Mario Geiger", "Stefano Spigler", "Gerard Arous", "Chiara Cammarota", "Yann LeCun", "Matthieu Wyart", "Giulio Biroli"], "The Well-Tempered Lasso": ["Yuanzhi Li", "Yoram Singer"], "Optimization, fast and slow: optimally switching between local and Bayesian optimization": ["Mark McLeod", "Stephen Roberts", "Michael A Osborne"], "Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care": ["Patrick Schwab", "Emanuela Keller", "Carl Muroi", "David J. Mack", "Christian Str\u00e4ssle", "Walter Karlen"], "Communication-Computation Efficient Gradient Coding": ["Min Ye", "Emmanuel Abbe"], "Escaping Saddles with Stochastic Gradients": ["Hadi Daneshmand", "Jonas Kohler", "Aurelien Lucchi", "Thomas Hofmann"], "Learning in Reproducing Kernel Kre\u0131\u0306n Spaces": ["Dino Oglic", "Thomas Gaertner"], "Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data": ["Amjad Almahairi", "Sai Rajeswar", "Alessandro Sordoni", "Philip Bachman", "Aaron Courville"], "Learning to Explain: An Information-Theoretic Perspective on Model Interpretation": ["Jianbo Chen", "Le Song", "Martin Wainwright", "Michael Jordan"], "Mix & Match - Agent Curricula for Reinforcement Learning": ["Wojciech Czarnecki", "Siddhant Jayakumar", "Max Jaderberg", "Leonard Hasenclever", "Yee Teh", "Nicolas Heess", "Simon Osindero", "Razvan Pascanu"], "Noise2Noise: Learning Image Restoration without Clean Data": ["Jaakko Lehtinen", "Jacob Munkberg", "Jon Hasselgren", "Samuli Laine", "Tero Karras", "Miika Aittala", "Timo Aila"], "Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization": ["Umut Simsekli", "Cagatay Yildiz", "Thanh Huy Nguyen", "Ali Taylan Cemgil", "Ga\u00ebl RICHARD"], "Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?": ["Lin Chen", "Moran Feldman", "Amin Karbasi"], "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning": ["Ahmed M. Alaa Ibrahim", "M van der Schaar"], "Analyzing Uncertainty in Neural Machine Translation": ["Myle Ott", "Michael Auli", "David Grangier", "Marc'Aurelio Ranzato"], "Distilling the Posterior in Bayesian Neural Networks": ["Kuan-Chieh Wang", "Paul Vicol", "James Lucas", "Li Gu", "Roger Grosse", "Richard Zemel"], "Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing": ["Davide Bacciu", "Federico Errica", "Alessio Micheli"], "Towards Black-box Iterative Machine Teaching": ["Weiyang Liu", "Bo Dai", "Xingguo Li", "Zhen Liu", "James Rehg", "Le Song"], "Structured Output Learning with Abstention: Application to Accurate Opinion Prediction": ["Alexandre Garcia", "Telecom-ParisTech Chlo\u00e9 Clavel", "Slim Essid", "Florence d'Alche-Buc"], "Ultra Large-Scale Feature Selection using Count-Sketches": ["Amirali Aghazadeh", "Ryan Spring", "Daniel LeJeune", "Gautam Dasarathy", "Anshumali Shrivastava", "Richard Baraniuk"], "Online Learning with Abstention": ["Corinna Cortes", "Giulia DeSalvo", "Claudio Gentile", "Mehryar Mohri", "Scott Yang"], "Topological mixture estimation": ["Steve Huntsman"], "Linear Spectral Estimators and an Application to Phase Retrieval": ["Ramina Ghods", "Andrew Lan", "Tom Goldstein", "Christoph Studer"], "Deep One-Class Classification": ["Lukas Ruff", "Nico G\u00f6rnitz", "Lucas Deecke", "Shoaib Ahmed Siddiqui", "Robert Vandermeulen", "Alexander Binder", "Emmanuel M\u00fcller", "Marius Kloft"], "End-to-end Active Object Tracking via Reinforcement Learning": ["Wenhan Luo", "Peng Sun", "Fangwei Zhong", "Wei Liu", "Tong Zhang", "Yizhou Wang"], "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness": ["Michael Kearns", "Seth V Neel", "Aaron Roth", "Zhiwei Wu"], "Practical Contextual Bandits with Regression Oracles": ["Dylan Foster", "Alekh Agarwal", "Miroslav Dudik", "Haipeng Luo", "Robert Schapire"], "Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks": ["Minmin Chen", "Jeffrey Pennington", "Samuel Schoenholz"], "Chi-square Generative Adversarial Network": ["Chenyang Tao", "Liqun Chen", "Ricardo Henao", "Jianfeng Feng", "Lawrence Carin"], "Fast Information-theoretic Bayesian Optimisation": ["Binxin Ru", "Michael A Osborne", "Mark Mcleod", "Diego Granziol"], "Data Summarization at Scale: A Two-Stage Submodular Approach": ["Marko Mitrovic", "Ehsan Kazemi", "Morteza Zadimoghaddam", "Amin Karbasi"], "Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings": ["Aviral Kumar", "Sunita Sarawagi", "Ujjwal Jain"], "Measuring abstract reasoning in neural networks": ["Adam Santoro", "Feilx Hill", "David GT Barrett", "Ari S Morcos", "Timothy Lillicrap"], "Bucket Renormalization for Approximate Inference": ["Sung-Soo Ahn", "Michael Chertkov", "Adrian Weller", "Jinwoo Shin"], "Inference Suboptimality in Variational Autoencoders": ["Chris Cremer", "Xuechen Li", "David Duvenaud"], "Weightless: Lossy weight encoding for deep neural network compression": ["Brandon Reagen", "Udit Gupta", "Bob Adolf", "Michael Mitzenmacher", "Alexander Rush", "Gu-Yeon Wei", "David Brooks"], "Optimization Landscape and Expressivity of Deep CNNs": ["Quynh Nguyen", "Matthias Hein"], "Efficient end-to-end learning for quantizable representations": ["Yeonwoo Jeong", "Hyun Oh Song"], "Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors": ["Soumya Ghosh", "Jiayu Yao", "Finale Doshi-Velez"], "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks": ["Zhao Chen", "Vijay Badrinarayanan", "Chen-Yu Lee", "Andrew Rabinovich"], "Residual Unfairness in Fair Machine Learning from Prejudiced Data": ["Nathan Kallus", "Angela Zhou"], "The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference": ["Hao Lu", "Yuan Cao", "Junwei Lu", "Han Liu", "Zhaoran Wang"], "Predict and Constrain: Modeling Cardinality in Deep Structured Prediction": ["Nataly Brukhim", "Amir Globerson"], "An Alternative View: When Does SGD Escape Local Minima?": ["Bobby Kleinberg", "Yuanzhi Li", "Yang Yuan"], "Tropical Geometry of Deep Neural Networks": ["Liwen Zhang", "Gregory Naisat", "Lek-Heng Lim"], "Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order": ["Vladimir Braverman", "Stephen Chestnut", "Robert Krauthgamer", "Yi Li", "David Woodruff", "Lin Yang"], "Adversarial Learning with Local Coordinate Coding": ["Jiezhang Cao", "Yong Guo", "Qingyao Wu", "Chunhua Shen", "Junzhou Huang", "Mingkui Tan"], "Compressing Neural Networks using the Variational Information Bottelneck": ["Bin Dai", "Chen Zhu", "Baining Guo", "David Wipf"], "A Spline Theory of Deep Learning": ["Randall Balestriero", "Richard Baraniuk"], "Semi-Supervised Learning on Data Streams via Temporal Label Propagation": ["Tal Wagner", "Sudipto Guha", "Shiva Kasiviswanathan", "Nina Mishra"], "Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information": ["Yichong Xu", "Hariank Muthakana", "Sivaraman Balakrishnan", "Aarti Singh", "Artur Dubrawski"], "Continuous-Time Flows for Efficient Inference and Density Estimation": ["Changyou Chen", "Chunyuan Li", "Liquan Chen", "Wenlin Wang", "Yunchen Pu", "Lawrence Carin"], "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam": ["Mohammad Emtiyaz Khan", "Didrik Nielsen", "Voot Tangkaratt", "Wu Lin", "Yarin Gal", "Akash Srivastava"], "A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations": ["Weili Nie", "Yang Zhang", "Ankit Patel"], "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory": ["Ron Amit", "Ron Meir"], "Local Density Estimation in High Dimensions": ["Xian Wu", "Moses Charikar", "Vishnu Natchu"], "Convergence guarantees for a class of non-convex and   non-smooth optimization problems": ["Koulik Khamaru", "Martin Wainwright"], "RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks": ["Jinsung Yoon", "James Jordon", "Mihaela van der Schaar"], "Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks": ["Brenden Lake", "Marco Baroni"], "Visualizing and Understanding Atari Agents": ["Samuel Greydanus", "Anurag Koul", "Jonathan Dodge", "Alan Fern"], "Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits": ["Zeyuan Allen-Zhu", "Sebastien Bubeck", "Yuanzhi Li"], "SGD and Hogwild! Convergence Without the Bounded Gradients Assumption": ["Lam Nguyen", "PHUONG HA NGUYEN", "Marten van Dijk", "Peter Richtarik", "Katya Scheinberg", "Martin Takac"], "Convergent Tree Backup and Retrace with Function Approximation": ["Ahmed Touati", "Pierre-Luc Bacon", "Doina Precup", "Pascal Vincent"], "Conditional Noise-Contrastive Estimation of Unnormalised Models": ["Ciwan Ceylan", "Michael Gutmann"], "Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers": ["Yao Ma", "Alexander Olshevsky", "Csaba Szepesvari", "Venkatesh Saligrama"], "GAIN: Missing Data Imputation using Generative Adversarial Nets": ["Jinsung Yoon", "James Jordon", "Mihaela van der Schaar"], "Bounds on the Approximation Power of Feedforward Neural Networks": ["Mohammad Mehrabi", "Aslan Tchamkerten", "MANSOOR I YOUSEFI"], "Neural Program Synthesis from Diverse Demonstration Videos": ["Shao-Hua Sun", "Hyeonwoo Noh", "Sriram Somasundaram", "Joseph Lim"], "An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning": ["Dhruv Malik", "Malayandi Palaniappan", "Jaime Fisac", "Dylan Hadfield-Menell", "Stuart Russell", "EECS Anca Dragan"], "Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement": ["Andre Barreto", "Diana Borsa", "John Quan", "Tom Schaul", "David Silver", "Matteo Hessel", "Daniel J. Mankowitz", "Augustin Zidek", "Remi Munos"], "Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis": ["Hiroyuki Kasai", "Hiroyuki Sato", "Bamdev Mishra"], "Tempered Adversarial Networks": ["Mehdi S. M. Sajjadi", "Giambattista Parascandolo", "Arash Mehrjou", "Bernhard Sch\u00f6lkopf"], "Policy Optimization with Demonstrations": ["Bingyi Kang", "Zequn Jie", "Jiashi Feng"], "Learning Registered Point Processes from Idiosyncratic Observations": ["Hongteng Xu", "Lawrence Carin", "Hongyuan Zha"], "Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks": ["Zhihao Jia", "Sina Lin", "Charles Qi", "Alex Aiken"], "Regret Minimization for Partially Observable Deep Reinforcement Learning": ["Peter Jin", "EECS Kurt Keutzer", "Sergey Levine"], "The Generalization Error of Dictionary Learning with Moreau Envelopes": ["ALEXANDROS GEORGOGIANNIS"], "Towards Fast Computation of Certified Robustness for ReLU Networks": ["Tsui-Wei (Lily) Weng", "Huan Zhang", "Hongge Chen", "Zhao Song", "Cho-Jui Hsieh", "Luca Daniel", "Duane Boning", "Inderjit Dhillon"], "Optimizing the Latent Space of Generative Networks": ["Piotr Bojanowski", "Armand Joulin", "David Lopez-Paz", "Arthur Szlam"], "DCFNet: Deep Neural Network with Decomposed Convolutional Filters": ["Qiang Qiu", "Xiuyuan Cheng", "robert Calderbank", "Guillermo Sapiro"], "Smoothed Action Value Functions for Learning Gaussian Policies": ["Ofir Nachum", "Mohammad Norouzi", "George Tucker", "Dale Schuurmans"], "Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron": ["RJ Skerry-Ryan", "Eric Battenberg", "Ying Xiao", "Yuxuan Wang", "Daisy Stanton", "Joel Shor", "Ron Weiss", "Robert Clark", "Rif Saurous"], "Constant-Time Predictive Distributions for Gaussian Processes": ["Geoff Pleiss", "Jacob Gardner", "Kilian Weinberger", "Andrew Wilson"], "Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control": ["Yangchen Pan", "Amir-massoud Farahmand", "Martha White", "Saleh Nabi", "Piyush Grover", "Daniel Nikovski"], "Binary Classification with Karmic, Threshold-Quasi-Concave Metrics": ["Bowei Yan", "Sanmi Koyejo", "Kai Zhong", "Pradeep Ravikumar"], "Robust and Scalable Models of Microbiome Dynamics": ["Travis Gibson", "Georg Gerber"], "Stochastic Variance-Reduced Policy Gradient": ["Matteo Papini", "Damiano Binaghi", "Giuseppe Canonaco", "Matteo Pirotta", "Marcello Restelli"], "Differentiable Abstract Interpretation for Provably Robust Neural Networks": ["Matthew Mirman", "Timon Gehr", "Martin Vechev"], "Differentially Private Matrix Completion Revisited": ["Prateek Jain", "Om Dipakbhai Thakkar", "Abhradeep Thakurta"], "Configurable Markov Decision Processes": ["Alberto Maria Metelli", "Mirco Mutti", "Marcello Restelli"], "Hierarchical Text Generation and Planning for Strategic Dialogue": ["Denis Yarats", "Mike Lewis"], "Conditional Neural Processes": ["Marta Garnelo", "Dan Rosenbaum", "Chris Maddison", "Tiago Ramalho", "David Saxton", "Murray Shanahan", "Yee Teh", "Danilo J. Rezende", "S. M. Ali Eslami"], "Functional Gradient Boosting based on Residual Network Perception": ["Atsushi Nitanda", "Taiji Suzuki"], "Distributed Nonparametric Regression under Communication Constraints": ["Yuancheng Zhu", "John Lafferty"], "Learning a Mixture of Two Multinomial Logits": ["Flavio Chierichetti", "Ravi Kumar", "Andrew Tomkins"], "Testing Sparsity over Known and Unknown Bases": ["Siddharth Barman", "Arnab Bhattacharyya", "Suprovat Ghoshal"], "Tree Edit Distance Learning via Adaptive Symbol Embeddings": ["Benjamin Paa\u00dfen", "Claudio Gallicchio", "Alessio Micheli", "CITEC Barbara Hammer"], "DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding": ["Thomas Moreau", "Laurent Oudre", "Nicolas Vayatis"], "Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction": ["Siyuan Qi", "Baoxiong Jia", "Song-Chun Zhu"], "Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks": ["Peter Bartlett", "Dave Helmbold", "Phil Long"], "Learning by Playing - Solving Sparse Reward Tasks from Scratch": ["Martin Riedmiller", "Roland Hafner", "Thomas Lampe", "Michael Neunert", "Jonas Degrave", "Tom Van de Wiele", "Vlad Mnih", "Nicolas Heess", "Jost Springenberg"], "State Space Gaussian Processes with Non-Gaussian Likelihood": ["Hannes Nickisch", "Arno Solin", "Alexander Grigorevskiy"], "ContextNet: Deep learning for Star Galaxy Classification": ["Noble Kennamer", "University of California David Kirkby", "Alexander Ihler", "University of California Francisco Javier Sanchez-Lopez"], "Best Arm Identification in Linear Bandits with Linear Dimension Dependency": ["Chao Tao", "Sa\u00fal A. Blanco", "Yuan Zhou"], "Randomized Block Cubic Newton Method": ["Nikita Doikov", "Peter Richtarik"], "Gradually Updated Neural Networks for Large-Scale Image Recognition": ["Siyuan Qiao", "Zhishuai Zhang", "Wei Shen", "Bo Wang", "Alan Yuille"], "Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for  Nonconvex Distributed Optimization Over Networks": ["Mingyi Hong", "Meisam Razaviyayn", "Jason Lee"], "Is Generator Conditioning Causally Related to GAN Performance?": ["Augustus Odena", "Jacob Buckman", "Catherine Olsson", "Tom B Brown", "Christopher Olah", "Colin Raffel", "Ian Goodfellow"], "Semiparametric Contextual Bandits": ["Akshay Krishnamurthy", "Zhiwei Wu", "Vasilis Syrgkanis"], "Differentially Private Database Release via Kernel Mean Embeddings": ["Matej Balog", "Ilya Tolstikhin", "Bernhard Sch\u00f6lkopf"], "Adaptive Three Operator Splitting": ["Fabian Pedregosa", "Gauthier Gidel"], "Learning Dynamics of Linear Denoising Autoencoders": ["Arnu Pretorius", "Steve Kroon", "Herman Kamper"], "Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy": ["Jiasen Yang", "Qiang Liu", "Vinayak A Rao", "Jennifer Neville"], "DiCE: The Infinitely Differentiable Monte Carlo Estimator": ["Jakob Foerster", "Gregory Farquhar", "Maruan Al-Shedivat", "Tim Rockt\u00e4schel", "Eric Xing", "Shimon Whiteson"], "Differentiable plasticity: training plastic neural networks with backpropagation": ["Thomas Miconi", "Kenneth Stanley", "Jeff Clune"], "Hierarchical Long-term Video Prediction without Supervision": ["Nevan Wichers", "Ruben Villegas", "Dumitru Erhan", "Honglak Lee"], "A Unified Framework for Structured Low-rank Matrix Learning": ["Pratik Kumar Jawanpuria", "Bamdev Mishra"], "IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures": ["Lasse Espeholt", "Hubert Soyer", "Remi Munos", "Karen Simonyan", "Vlad Mnih", "Tom Ward", "Yotam Doron", "Vlad Firoiu", "Tim Harley", "Iain Dunning", "Shane Legg", "koray kavukcuoglu"], "Synthesizing Programs for Images using Reinforced Adversarial Learning": ["Iaroslav Ganin", "Tejas Kulkarni", "Igor Babuschkin", "S. M. Ali Eslami", "Oriol Vinyals"], "The Uncertainty Bellman Equation and Exploration": ["Brendan O'Donoghue", "Ian Osband", "Remi Munos", "Vlad Mnih"], "Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design": ["Wenlong Lyu", "Fan Yang", "Changhao Yan", "Dian Zhou", "Xuan Zeng"], "Noisy Natural Gradient as Variational Inference": ["Guodong Zhang", "Shengyang Sun", "David Duvenaud", "Roger Grosse"], "Path Consistency Learning in Tsallis Entropy Regularized MDPs": ["Yinlam Chow", "Ofir Nachum", "Mohammad Ghavamzadeh"], "Learning Independent Causal Mechanisms": ["Giambattista Parascandolo", "Niki Kilbertus", "Mateo Rojas-Carulla", "Bernhard Sch\u00f6lkopf"], "Differentiable Compositional Kernel Learning for Gaussian Processes": ["Shengyang Sun", "Guodong Zhang", "Chaoqi Wang", "Wenyuan Zeng", "Jiaman Li", "Roger Grosse"], "Analyzing the Robustness of Nearest Neighbors to Adversarial Examples": ["Yizhen Wang", "Somesh Jha", "Kamalika Chaudhuri"], "TACO: Learning Task Decomposition via Temporal Alignment for Control": ["Kyriacos Shiarlis", "Markus Wulfmeier", "Sasha Salter", "Shimon Whiteson", "Herbert Ingmar Posner"], "Out-of-sample extension of graph adjacency spectral embedding": ["Keith Levin", "Fred Roosta", "Michael Mahoney", "Carey Priebe"], "Ranking Distributions based on Noisy Sorting": ["Adil El Mesaoudi-Paul", "Eyke H\u00fcllermeier", "Robert Busa-Fekete"], "An Inference-Based Policy Gradient Method for Learning Options": ["Matthew Smith", "Herke van Hoof", "Joelle Pineau"], "Improving Optimization in Models With Continuous Symmetry Breaking": ["Robert Bamler", "Stephan Mandt"], "Kernelized Synaptic Weight Matrices": ["Lorenz M\u00fcller", "Julien Martel", "Giacomo Indiveri"], "$D^2$: Decentralized Training over Decentralized Data": ["Hanlin Tang", "Xiangru Lian", "Ming Yan", "Ce Zhang", "Ji Liu"], "A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates": ["Kaiwen Zhou", "Fanhua Shang", "James Cheng"], "The Power of Interpolation:  Understanding the Effectiveness of SGD in Modern Over-parametrized Learning": ["Siyuan Ma", "Raef Bassily", "Mikhail Belkin"], "On Nesting Monte Carlo Estimators": ["Tom Rainforth", "Rob Cornish", "Hongseok Yang", "andrew warrington", "Frank Wood"], "Learning in Integer Latent Variable Models with Nested Automatic Differentiation": ["Daniel Sheldon", "Kevin Winner", "Debora Sujono"], "Learning to Act in Decentralized Partially Observable MDPs": ["Jilles Dibangoye", "Olivier Buffet"], "An Iterative, Sketching-based Framework for Ridge Regression": ["Agniva Chowdhury", "Jiasen Yang", "Petros Drineas"], "Generative Temporal Models with Spatial Memory for Partially Observed Environments": ["Marco Fraccaro", "Danilo J. Rezende", "Yori Zwols", "Alexander Pritzel", "S. M. Ali Eslami", "Fabio Viola"], "Synthesizing Robust Adversarial Examples": ["Anish Athalye", "Logan Engstrom", "Andrew Ilyas", "Kevin Kwok"], "Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations": ["Ting Chen", "Martin Min", "Yizhou Sun"], "Recurrent Predictive State Policy Networks": ["Ahmed Hefny", "Zita Marinho", "Wen Sun", "Siddhartha Srinivasa", "Geoff Gordon"], "Open Category Detection with PAC Guarantees": ["Si Liu", "Risheek Garrepalli", "Thomas Dietterich", "Alan Fern", "Dan Hendrycks"], "On the Implicit Bias of Dropout": ["Poorya Mianjy", "Raman Arora", "Rene Vidal"], "Implicit Quantile Networks for Distributional Reinforcement Learning": ["Will Dabney", "Georg Ostrovski", "David Silver", "Remi Munos"], "Variational Bayesian dropout: pitfalls and fixes": ["Jiri Hron", "Alexander Matthews", "Zoubin Ghahramani"], "Stagewise Safe Bayesian Optimization with Gaussian Processes": ["Yanan Sui", "Vincent Zhuang", "Joel Burdick", "Yisong Yue"], "On Matching Pursuit and Coordinate Descent": ["Francesco Locatello", "Anant Raj", "Sai Praneeth Reddy Karimireddy", "Gunnar Raetsch", "Bernhard Sch\u00f6lkopf", "Sebastian Stich", "Martin Jaggi"], "Large-Scale Cox Process Inference using Variational Fourier Features": ["ST John", "James Hensman"], "Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces": ["Junhong Lin", "Volkan Cevher"], "Semi-Implicit Variational Inference": ["Mingzhang Yin", "Mingyuan Zhou"], "Fixing a Broken ELBO": ["Alexander Alemi", "Ben Poole", "Ian Fischer", "Joshua V Dillon", "Rif Saurous", "Kevin Murphy"], "Black Box FDR": ["Wesley Tansey", "Yixin Wang", "David Blei", "Raul Rabadan"], "Bayesian Optimization of Combinatorial Structures": ["Ricardo Baptista", "Matthias Poloczek"], "Nonoverlap-Promoting Variable Selection": ["Pengtao Xie", "Hongbao Zhang", "Yichen Zhu", "Eric Xing"], "Structured Evolution with Compact Architectures for Scalable Policy Optimization": ["Krzysztof Choromanski", "Mark Rowland", "Vikas Sindhwani", "Richard E Turner", "Adrian Weller"], "Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap": ["Miles Lopes", "Shusen Wang", "Michael Mahoney"], "Invariance of Weight Distributions in Rectified MLPs": ["Susumu Tsuchida", "Fred Roosta", "Marcus Gallagher"], "Autoregressive Convolutional Neural Networks for Asynchronous Time Series": ["Mikolaj Binkowski", "Gautier Marti", "Philippe Donnat"], "Causal Bandits with Propagating Inference": ["Akihiro Yabe", "Daisuke Hatano", "Hanna Sumita", "Shinji Ito", "Naonori Kakimura", "Takuro Fukunaga", "Ken-ichi Kawarabayashi"], "CRVI: Convex Relaxation for Variational Inference": ["Ghazal Fazelnia", "John Paisley"], "Probabilistic Boolean Tensor Decomposition": ["Tammo Rukat", "Christopher Holmes", "Christopher Yau"], "Convolutional Imputation of Matrix Networks": ["Qingyun Sun", "Mengyuan Yan", "David Donoho", "stephen boyd"], "An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks": ["Qianxiao Li", "IHPC Shuji Hao"], "Learning equations for extrapolation and control": ["Subham S Sahoo", "Christoph Lampert", "Georg Martius"], "Multicalibration: Calibration for the (Computationally-Identifiable) Masses": ["Ursula Hebert-Johnson", "Michael Kim", "Omer Reingold", "Guy Rothblum"], "Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems": ["Eugenio Bargiacchi", "Timothy Verstraeten", "Diederik Roijers", "Ann Now\u00e9", "Hado van Hasselt"], "A Two-Step Computation of the Exact GAN Wasserstein Distance": ["Huidong Liu", "Xianfeng GU", "Samaras Dimitris"], "Learning with Abandonment": ["Sven Schmit", "Ramesh Johari"], "Network Global Testing by Counting Graphlets": ["Jiashun Jin", "Zheng Ke", "Shengming Luo"], "Learning to Reweight Examples for Robust Deep Learning": ["Mengye Ren", "Wenyuan Zeng", "Bin Yang", "Raquel Urtasun"], "Learning Implicit Generative Models with the Method of Learned Moments": ["Suman Ravuri", "Shakir Mohamed", "Mihaela Rosca", "Oriol Vinyals"], "Learning Policy Representations in Multiagent Systems": ["Aditya Grover", "Maruan Al-Shedivat", "Jayesh Gupta", "Yura Burda", "Harrison Edwards"], "A Reductions Approach to Fair Classification": ["Alekh Agarwal", "Alina Beygelzimer", "Miroslav Dudik", "John Langford", "Hanna Wallach"], "Safe Element Screening for Submodular Function Minimization": ["Weizhong Zhang", "Bin Hong", "Lin Ma", "Wei Liu", "Tong Zhang"], "Modeling Sparse Deviations for Compressed Sensing using Generative Models": ["Manik Dhar", "Aditya Grover", "Stefano Ermon"], "Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent": ["Trevor Campbell", "Tamara Broderick"], "Dimensionality-Driven Learning with Noisy Labels": ["Xingjun Ma", "Yisen Wang", "Michael E. Houle", "Shuo Zhou", "Sarah Erfani", "Shutao Xia", "Sudanthi Wijewickrema", "James Bailey"], "A Classification-Based Study of Covariate Shift in GAN Distributions": ["Shibani Santurkar", "Ludwig Schmidt", "Aleksander Madry"], "Transformation Autoregressive Networks": ["Junier Oliva", "Kumar Avinava Dubey", "Manzil Zaheer", "Barnab\u00e1s P\u00f3czos", "Ruslan Salakhutdinov", "Eric Xing", "Jeff Schneider"], "prDeep: Robust Phase Retrieval with a Flexible Deep Network": ["Christopher Metzler", "Phillip Schniter", "Ashok Veeraraghavan", "Richard Baraniuk"], "Thompson Sampling for Combinatorial Semi-Bandits": ["Siwei Wang", "Wei Chen"], "Hierarchical Multi-Label Classification Networks": ["Jonatas Wehrmann", "Ricardo Cerri", "Rodrigo Barros"], "PDE-Net: Learning PDEs from Data": ["Zichao Long", "Yiping Lu", "Xianzhong Ma", "Bin Dong"], "Modeling Others using Oneself in Multi-Agent Reinforcement Learning": ["Roberta Raileanu", "Emily Denton", "Arthur Szlam", "Facebook Rob Fergus"], "Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data": ["Minyoung Kim"], "Composable Planning with Attributes": ["Amy Zhang", "Sainbayar Sukhbaatar", "Adam Lerer", "Arthur Szlam", "Facebook Rob Fergus"], "Provable Variable Selection for Streaming Features": ["Jing Wang", "Jie Shen", "Ping Li"], "Approximation Guarantees for Adaptive Sampling": ["Eric Balkanski", "Yaron Singer"], "Learning long term dependencies via Fourier recurrent units": ["Jiong Zhang", "Yibo Lin", "Zhao Song", "Inderjit Dhillon"], "Accelerating Greedy Coordinate Descent Methods": ["Haihao Lu", "Robert Freund", "Vahab Mirrokni"], "Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer": ["Alexey Drutsa"], "Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems": ["Marc Abeille", "Alessandro Lazaric"], "Coordinated Exploration in Concurrent Reinforcement Learning": ["Maria Dimakopoulou", "Benjamin Van Roy"], "Disentangling by Factorising": ["Hyunjik Kim", "Andriy Mnih"], "Mitigating Bias in Adaptive Data Gathering via Differential Privacy": ["Seth V Neel", "Aaron Roth"], "Structured Variationally Auto-encoded Optimization": ["Xiaoyu Lu", "Javier Gonz\u00e1lez", "Zhenwen Dai", "Neil Lawrence"], "Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time": ["Asish Ghoshal", "Jean Honorio"], "Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization": ["Ibrahim Alabdulmohsin"], "Efficient and Consistent Adversarial Bipartite Matching": ["Rizal Fathony", "Sima Behpour", "Xinhua Zhang", "Brian Ziebart"], "Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs": ["Andrea Zanette", "Emma Brunskill"], "Black-Box Variational Inference for Stochastic Differential Equations": ["Tom Ryder", "Andrew Golightly", "Stephen McGough", "Dennis Prangle"], "Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches": ["Simon Olofsson", "Marc P Deisenroth", "Ruth Misener"], "Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices": ["Zengfeng Huang"], "Geometry Score: A Method For Comparing Generative Adversarial Networks": ["Valentin Khrulkov", "Ivan Oseledets"], "MAGAN: Aligning Biological Manifolds": ["Matt Amodio", "Smita Krishnaswamy"], "Understanding the Loss Surface of Neural Networks for Binary Classification": ["SHIYU LIANG", "Ruoyu Sun", "Yixuan Li", "R Srikant"], "Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope": ["Eric Wong", "Zico Kolter"], "Improved Training of Generative Adversarial Networks Using Representative Features": ["Duhyeon Bang", "Hyunjung Shim"], "Detecting non-causal artifacts in multivariate linear regression models": ["Dominik Janzing", "Bernhard Sch\u00f6lkopf"], "Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization": ["Jiaxiang Wu", "Weidong Huang", "Junzhou Huang", "Tong Zhang"], "Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization": ["Jinghui Chen", "Pan Xu", "Lingxiao Wang", "Jian Ma", "Quanquan Gu"], "The Hierarchical Adaptive Forgetting Variational Filter": ["Vincent Moens"], "Fast Decoding in Sequence Models Using Discrete Latent Variables": ["Lukasz Kaiser", "Samy Bengio", "Aurko Roy", "Ashish Vaswani", "Niki Parmar", "Jakob Uszkoreit", "Noam Shazeer"], "Revealing Common Statistical Behaviors in Heterogeneous Populations": ["Andrey Zhitnikov", "Rotem Mulayoff", "Tomer Michaeli"], "Unbiased Objective Estimation in Predictive Optimization": ["Shinji Ito", "Akihiro Yabe", "Ryohei Fujimaki"], "Fast Parametric Learning with Activation Memorization": ["Jack Rae", "Chris Dyer", "Peter Dayan", "Timothy Lillicrap"], "Stein Points": ["Wilson Ye Chen", "Lester Mackey", "Jackson Gorham", "Francois-Xavier Briol", "Chris J Oates"], "Using Inherent Structures to design Lean 2-layer RBMs": ["Abhishek Bansal", "Abhinav Anand", "Chiranjib Bhattacharyya"], "SparseMAP: Differentiable Sparse Structured Inference": ["Vlad Niculae", "Andre Filipe Torres Martins", "Mathieu Blondel", "Claire Cardie"], "Video Prediction with Appearance and Motion Conditions": ["Yunseok Jang", "Gunhee Kim", "Yale Song"], "Programmatically Interpretable Reinforcement Learning": ["Abhinav Verma", "Vijayaraghavan Murali", "Rishabh Singh", "Pushmeet Kohli", "Swarat Chaudhuri"], "Spline Filters For End-to-End Deep Learning": ["Randall Balestriero", "Romain Cosentino", "Herve Glotin", "Richard Baraniuk"], "Stochastic Training of Graph Convolutional Networks with Variance Reduction": ["Jianfei Chen", "Jun Zhu", "Le Song"], "Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework": ["Arman Sharifi Kolarijani", "Peyman Mohajerin Esfahani", "Tamas Keviczky"], "On the Limitations of First-Order Approximation in GAN Dynamics": ["Jerry Li", "Aleksander Madry", "John Peebles", "Ludwig Schmidt"], "SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate": ["Aaditya Ramdas", "Tijana Zrnic", "Martin Wainwright", "Michael Jordan"], "Approximation Algorithms for Cascading Prediction Models": ["Matthew Streeter"], "Adaptive Sampled Softmax with Kernel Based Sampling": ["Guy Blanc", "Steffen Rendle"], "Scalable approximate Bayesian inference for particle tracking data": ["Ruoxi Sun", "Department of Statistics Liam Paninski"], "Learning to Speed Up Structured Output Prediction": ["Xingyuan Pan", "Vivek Srikumar"], "Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning": ["Rodrigo A Toro Icarte", "Toryn Q Klassen", "Richard Valenzano", "Sheila McIlraith"], "Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing\u2014and Back": ["Elliot Meyerson", "Risto Miikkulainen"], "Let\u2019s be Honest: An Optimal No-Regret Framework for Zero-Sum Games": ["Ehsan Asadi Kangarshahi", "Ya-Ping Hsieh", "Mehmet Fatih Sahin", "Volkan Cevher"], "Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm": ["Pavel Dvurechenskii", "Alexander Gasnikov", "Alexey Kroshnin"], "Feedback-Based Tree Search for Reinforcement Learning": ["Daniel Jiang", "Emmanuel Ekwedike", "Han Liu"], "Clipped Action Policy Gradient": ["Yasuhiro Fujita", "Shin-ichi Maeda"], "Improved large-scale graph learning through ridge spectral sparsification": ["Daniele Calandriello", "Alessandro Lazaric", "Ioannis Koutis", "Michal Valko"], "Progress & Compress: A scalable framework for continual learning": ["Jonathan Schwarz", "Wojciech Czarnecki", "Jelena Luketina", "Agnieszka Grabska-Barwinska", "Yee Teh", "Razvan Pascanu", "Raia Hadsell"], "Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach": ["Mao Ye", "Yan Sun"], "High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach": ["Tim Pearce", "Alexandra Brintrup", "Mohamed Zaki", "Andy Neely"], "Learning Representations and Generative Models for 3D Point Clouds": ["Panagiotis Achlioptas", "Olga Diamanti", "Ioannis Mitliagkas", "Leonidas Guibas"], "Geodesic Convolutional Shape Optimization": ["Pierre Baque", "Edoardo Remelli", "Francois Fleuret", "EPFL Pascal Fua"], "Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization": ["Louis Filstroff", "Alberto Lumbreras", "Cedric Fevotte"], "Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression": ["Haitao Liu", "Jianfei Cai", "Yi Wang", "Yew Soon ONG"], "K-means clustering using random matrix sparsification": ["Kaushik Sinha"], "Yes, but Did It Work?: Evaluating Variational Inference": ["Yuling Yao", "Aki Vehtari", "Daniel Simpson", "Andrew Gelman"], "On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups": ["Risi Kondor", "Shubhendu Trivedi"], "BOCK : Bayesian Optimization with Cylindrical Kernels": ["ChangYong Oh", "Efstratios Gavves", "Max Welling"], "Addressing Function Approximation Error in Actor-Critic Methods": ["Scott Fujimoto", "Herke van Hoof", "David Meger"], "Locally Private Hypothesis Testing": ["Or Sheffet"], "Focused Hierarchical RNNs for Conditional Sequence Processing": ["Rosemary Nan Ke", "Konrad Zolna", "Alessandro Sordoni", "MILA Zhouhan Lin", "Adam Trischler", "Yoshua Bengio", "Joelle Pineau", "Laurent Charlin", "Christopher Pal"], "WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models": ["Marine LE MORVAN", "Jean-Philippe Vert"], "Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions": ["Karren Yang", "Abigail Katoff", "Caroline Uhler"], "Estimation of Markov Chain via Rank-constrained Likelihood": ["XUDONG LI", "Mengdi Wang", "Anru Zhang"], "Accelerating Natural Gradient with Higher-Order Invariance": ["Yang Song", "Jiaming Song", "Stefano Ermon"], "Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees": ["Adrien Taylor", "Bryan Van Scoy", "Laurent Lessard"], "On Learning Sparsely Used Dictionaries from Incomplete Samples": ["Thanh Nguyen", "Akshay Soni", "Chinmay Hegde"], "Mixed batches and symmetric discriminators for GAN training": ["Thomas LUCAS", "Corentin Tallec", "Yann Ollivier", "Jakob Verbeek"], "Distributed Clustering via LSH Based Data Partitioning": ["Aditya Bhaskara", "Pruthuvi Wijewardena"], "Training Neural Machines with Trace-Based Supervision": ["Matthew Mirman", "Dimitar Dimitrov", "Pavle Djordjevic", "Timon Gehr", "Martin Vechev"], "Fitting New Speakers Based on a Short Untranscribed Sample": ["Eliya Nachmani", "Adam Polyak", "Yaniv Taigman", "Lior Wolf"], "ADMM and Accelerated ADMM as Continuous Dynamical Systems": ["Guilherme Franca", "Daniel Robinson", "Rene Vidal"], "Neural Autoregressive Flows": ["Chin-Wei Huang", "David Krueger", "Alexandre Lacoste", "Aaron Courville"], "Composite Marginal Likelihood Methods for Random Utility Models": ["Zhibing Zhao", "Lirong Xia"], "Theoretical Analysis of Sparse Subspace Clustering with Missing Entries": ["Manolis Tsakiris", "Rene Vidal"], "Mean Field Multi-Agent Reinforcement Learning": ["Yaodong Yang", "Rui Luo", "Minne Li", "Ming Zhou", "Weinan Zhang", "Jun Wang"], "Characterizing Implicit Bias in Terms of Optimization Geometry": ["Suriya Gunasekar", "Jason Lee", "Daniel Soudry", "Nati Srebro"], "Dynamic Evaluation of Neural Sequence Models": ["Ben Krause", "Emmanuel Kahembwe", "Iain Murray", "Steve Renals"], "MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels": ["Lu Jiang", "Zhengyuan Zhou", "Thomas Leung", "Li-Jia Li", "Li Fei-Fei"], "Anonymous Walk Embeddings": ["Sergey Ivanov", "Evgeny Burnaev"], "Loss Decomposition for Fast Learning in Large Output Spaces": ["En-Hsu Yen", "Satyen Kale", "Felix Xinnan Yu", "Daniel Holtmann-Rice", "Sanjiv Kumar", "Pradeep Ravikumar"], "Representation Learning on Graphs with Jumping Knowledge Networks": ["Keyulu Xu", "Chengtao Li", "Yonglong Tian", "Tomohiro Sonobe", "Ken-ichi Kawarabayashi", "Stefanie Jegelka"], "On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo": ["Niladri S Chatterji", "Nicolas Flammarion", "Yian Ma", "Peter Bartlett", "Michael Jordan"], "Learning One Convolutional Layer with Overlapping Patches": ["Surbhi Goel", "Adam Klivans", "Raghu Meka"], "WSNet: Compact and Efficient Networks Through Weight Sampling": ["Xiaojie Jin", "Yingzhen Yang", "Ning Xu", "Jianchao Yang", "Nebojsa Jojic", "Jiashi Feng", "Shuicheng Yan"], "Tight Regret Bounds for Bayesian Optimization in One Dimension": ["Jonathan Scarlett"], "Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples": ["Gail Weiss", "Yoav Goldberg", "Eran Yahav"], "Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor": ["Tuomas Haarnoja", "Aurick Zhou", "Pieter Abbeel", "Sergey Levine"], "QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning": ["Tabish Rashid", "Mikayel Samvelyan", "Christian Schroeder", "Gregory Farquhar", "Jakob Foerster", "Shimon Whiteson"], "Structured Control Nets for Deep Reinforcement Learning": ["Mario Srouji", "Jian Zhang", "Ruslan Salakhutdinov"], "Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion": ["Cong Ma", "Kaizheng Wang", "Yuejie Chi", "Yuxin Chen"], "Temporal Poisson Square Root Graphical Models": ["Sinong Geng", "Zhaobin Kuang", "Peggy Peissig", "University of Wisconsin David Page"], "Do Outliers Ruin Collaboration?": ["Mingda Qiao"], "Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator": ["Stephen Tu", "Benjamin Recht"], "Decoupled Parallel Backpropagation with Convergence Guarantee": ["Zhouyuan Huo", "Bin Gu", "Qian Yang", "Heng Huang"], "A Robust Approach to Sequential Information Theoretic Planning": ["Sue Zheng", "Jason Pacheco", "John Fisher"], "Efficient Gradient-Free Variational Inference using Policy Search": ["Oleg Arenz", "Gerhard Neumann", "Mingjun Zhong"], "Hierarchical Imitation and Reinforcement Learning": ["Hoang M Le", "Nan Jiang", "Alekh Agarwal", "Miroslav Dudik", "Yisong Yue", "Hal Daume"], "Learning Semantic Representations for Unsupervised Domain Adaptation": ["Shaoan Xie", "Zibin Zheng", "Liang Chen", "Chuan Chen"], "Graph Networks as Learnable Physics Engines for Inference and Control": ["Alvaro Sanchez", "Nicolas Heess", "Jost Springenberg", "Josh Merel", "Martin Riedmiller", "Raia Hadsell", "Peter Battaglia"], "Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines": ["Bin Gu", "Zhouyuan Huo", "Cheng Deng", "Heng Huang"], "Streaming Principal Component Analysis in Noisy Setting": ["Teodor Vanislavov Marinov", "Poorya Mianjy", "Raman Arora"], "Policy Optimization as Wasserstein Gradient Flows": ["RUIYI ZHANG", "Changyou Chen", "Chunyuan Li", "Lawrence Carin"], "Time Limits in Reinforcement Learning": ["Fabio Pardo", "Arash Tavakoli", "Vitaly Levdik", "Petar Kormushev"], "Non-convex Conditional Gradient Sliding": ["chao qu", "Yan Li", "Huan Xu"], "Adversarial Risk and the Dangers of Evaluating Against Weak Attacks": ["Jonathan Uesato", "Brendan O'Donoghue", "Pushmeet Kohli", "A\u00e4ron van den Oord"], "Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search": ["Masanori SUGANUMA", "Mete Ozay", "Takayuki Okatani"], "CyCADA: Cycle-Consistent Adversarial Domain Adaptation": ["Judy Hoffman", "Eric Tzeng", "Taesung Park", "Jun-Yan Zhu", "Philip Isola", "Kate Saenko", "Alexei Efros", "Trevor Darrell"], "Transfer Learning via Learning to Transfer": ["Ying WEI", "Yu Zhang", "Junzhou Huang", "Qiang Yang"], "Which Training Methods for GANs do actually Converge?": ["Lars Mescheder", "Andreas Geiger", "Sebastian Nowozin"], "Theoretical Analysis of Image-to-Image Translation with Adversarial Learning": ["Xudong Pan", "Mi Zhang", "Daizong Ding"], "Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling": ["kyowoon Lee", "Sol-A Kim", "Jaesik Choi", "Seong-Whan Lee"], "Spectrally Approximating Large Graphs with Smaller Graphs": ["Andreas Loukas", "Pierre Vandergheynst"], "Learning to Branch": ["Nina Balcan", "Travis Dick", "Tuomas Sandholm", "Ellen Vitercik"], "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples": ["Anish Athalye", "Nicholas Carlini", "David Wagner"], "Discovering Interpretable Representations for Both Deep Generative and Discriminative Models": ["Tameem Adel", "Zoubin Ghahramani", "Adrian Weller"], "Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors": ["Yichi Zhou", "Jun Zhu", "Jingwei Zhuo"], "Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates": ["Dong Yin", "Yudong Chen", "Kannan Ramchandran", "Peter Bartlett"], "Lipschitz Continuity in Model-based Reinforcement Learning": ["Kavosh Asadi", "Dipendra Misra", "Michael L. Littman"], "SADAGRAD: Strongly Adaptive Stochastic Gradient Methods": ["Zaiyi Chen", "Yi Xu", "Enhong Chen", "Tianbao Yang"], "Improved nearest neighbor search using auxiliary information and priority functions": ["Omid Keivani", "Kaushik Sinha"], "Prediction Rule Reshaping": ["Matt Bonakdarpour", "Sabyasachi Chatterjee", "Rina Barber", "John Lafferty"], "The Dynamics of Learning: A Random Matrix Approach": ["Zhenyu Liao", "Romain Couillet"], "BOHB: Robust and Efficient Hyperparameter Optimization at Scale": ["Stefan Falkner", "Aaron Klein", "Frank Hutter"], "Variational Network Inference: Strong and Stable with Concrete Support": ["Amir Dezfouli", "Edwin Bonilla", "Richard Nock"], "Been There, Done That: Meta-Learning with Episodic Recall": ["Samuel Ritter", "Jane Wang", "Zeb Kurth-Nelson", "Siddhant Jayakumar", "Charles Blundell", "Razvan Pascanu", "Matthew Botvinick"], "Parallel Bayesian Network Structure Learning": ["Tian Gao", "Dennis Wei"], "Crowdsourcing with Arbitrary Adversaries": ["Matth\u00e4us Kleindessner", "Pranjal Awasthi"], "A Distributed Second-Order Algorithm You Can Trust": ["Celestine D\u00fcnner", "Aurelien Lucchi", "Matilde Gargiani", "An Bian", "Thomas Hofmann", "Martin Jaggi"], "Fourier Policy Gradients": ["Matthew Fellows", "Kamil Ciosek", "Shimon Whiteson"], "On the Power of Over-parametrization in Neural Networks with Quadratic Activation": ["Simon Du", "Jason Lee"], "Efficient Neural Architecture Search via Parameters Sharing": ["Hieu Pham", "Melody Guan", "Barret Zoph", "Quoc Le", "Jeff Dean"], "Composite Functional Gradient Learning of Generative  Adversarial Models": ["Rie Johnson", "Tong Zhang"], "Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory": ["Guillaume Pouliot"], "Learning to search with MCTSnets": ["Arthur Guez", "Theophane Weber", "Ioannis Antonoglou", "Karen Simonyan", "Oriol Vinyals", "Daan Wierstra", "Remi Munos", "David Silver"], "NetGAN: Generating Graphs via Random Walks": ["Aleksandar Bojchevski", "Oleksandr Shchur", "Daniel Z\u00fcgner", "Stephan G\u00fcnnemann"], "Fast Variance Reduction Method with Stochastic Batch Size": ["University of California Xuanqing Liu", "Cho-Jui Hsieh"], "Investigating Human Priors for Playing Video Games": ["Rachit Dubey", "Pulkit Agrawal", "Deepak Pathak", "Tom Griffiths", "Alexei Efros"], "The Hidden Vulnerability of Distributed Learning in Byzantium": ["El Mahdi El Mhamdi", "Rachid Guerraoui", "S\u00e9bastien Rouault"], "Bayesian Model Selection for Change Point Detection and Clustering": ["othmane mazhar", "Cristian R. Rojas", "Inst. of Technology Carlo Fischione", "Mohammad Reza Hesamzadeh"], "Learning Steady-States of Iterative Algorithms over Graphs": ["Hanjun Dai", "Zornitsa Kozareva", "Bo Dai", "Alex Smola", "Le Song"], "Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients": ["Lukas Balles", "Philipp Hennig"], "Shampoo: Preconditioned Stochastic Tensor Optimization": ["Vineet Gupta", "Tomer Koren", "Yoram Singer"], "Spotlight: Optimizing Device Placement for Training Deep Neural Networks": ["Yuanxiang Gao", "Department of Electrical and Computer Li Chen", "Baochun Li"], "Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization": ["Hang Wu", "May Wang"], "Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations": ["IEMS Xingyu Wang", "Diego Klabjan"], "Parameterized Algorithms for the Matrix Completion Problem": ["Robert Ganian", "DePaul Iyad Kanj", "Sebastian Ordyniak", "Stefan Szeider"], "Classification from Pairwise Similarity and Unlabeled Data": ["Han Bao", "Gang Niu", "Masashi Sugiyama"], "Tighter Variational Bounds are Not Necessarily Better": ["Tom Rainforth", "Adam Kosiorek", "Tuan Anh Le", "Chris Maddison", "Maximilian Igl", "Frank Wood", "Yee Whye Teh"], "Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents": ["Kaiqing Zhang", "Zhuoran Yang", "Han Liu", "Tong Zhang", "Tamer Basar"], "Stochastic Video Generation with a Learned Prior": ["Emily Denton", "Rob Fergus"], "Semi-Supervised Learning via Compact Latent Space Clustering": ["Konstantinos Kamnitsas", "Daniel C. Castro", "Loic Le Folgoc", "Ian Walker", "Ryutaro Tanno", "Daniel Rueckert", "Ben Glocker", "Antonio Criminisi", "Aditya Nori"], "Competitive Caching with Machine Learned Advice": ["Thodoris Lykouris", "Sergei Vassilvitskii"], "DRACO: Byzantine-resilient Distributed Training via Redundant Gradients": ["Lingjiao Chen", "Hongyi Wang", "Zachary Charles", "Dimitris Papailiopoulos"], "Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication": ["Zebang Shen", "Aryan Mokhtari", "Tengfei Zhou", "Peilin Zhao", "Hui Qian"], "Learning Memory Access Patterns": ["Milad Hashemi", "Kevin Swersky", "Jamie Smith", "Grant Ayers", "Heiner Litz", "Jichuan Chang", "Christos Kozyrakis", "Parthasarathy Ranganathan"], "Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate": ["Mingrui Liu", "Xiaoxuan Zhang", "Zaiyi Chen", "Xiaoyu Wang", "Tianbao Yang"], "Hierarchical Clustering with Structural Constraints": ["Evangelos Chatziafratis", "Rad Niazadeh", "Moses Charikar"], "Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations": ["Ashwin Kalyan", "Stefan Lee", "Anitha Kannan", "Dhruv Batra"], "Essentially No Barriers in Neural Network Energy Landscape": ["Felix Draxler", "Kambis Veschgini", "Manfred Salmhofer", "Fred Hamprecht"], "Deep Density Destructors": ["David Inouye", "Pradeep Ravikumar"], "Approximate message passing for amplitude based optimization": ["Junjie Ma", "Ji Xu", "Arian Maleki"], "Gated Path Planning Networks": ["Lisa Lee", "Emilio Parisotto", "Devendra Singh Chaplot", "Eric Xing", "Ruslan Salakhutdinov"], "On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization": ["Sanjeev Arora", "Nadav Cohen", "Elad Hazan"], "Rates of Convergence of Spectral Methods for Graphon Estimation": ["Jiaming Xu"], "Feasible Arm Identification": ["Julian Katz-Samuels", "Clay Scott"], "Spurious Local Minima are Common in Two-Layer ReLU Neural Networks": ["Itay Safran", "Ohad Shamir"], "Self-Bounded Prediction Suffix Tree via Approximate String Matching": ["Dongwoo Kim", "Christian Walder"], "Frank-Wolfe with Subsampling Oracle": ["Thomas Kerdreux", "Fabian Pedregosa", "Alexandre d'Aspremont"], "Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions": ["Quynh Nguyen", "Mahesh Mukkamala", "Matthias Hein"], "Finding Influential Training Samples for Gradient Boosted Decision Trees": ["Boris Sharchilev", "Yury Ustinovskiy", "Pavel Serdyukov", "Maarten de Rijke"], "Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection": ["Jeremias Knoblauch", "Theodoros Damoulas"], "Deep Asymmetric Multi-task Feature Learning": ["Hae Beom Lee", "Eunho Yang", "Sung Ju Hwang"], "Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator": ["Maryam Fazel", "Rong Ge", "Sham Kakade", "Mehran Mesbahi"], "Max-Mahalanobis Linear Discriminant Analysis Networks": ["Tianyu Pang", "Chao Du", "Jun Zhu"], "A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning": ["Konstantin Mishchenko", "Franck Iutzeler", "J\u00e9r\u00f4me Malick", "Massih-Reza Amini"], "Rapid Adaptation with Conditionally Shifted Neurons": ["Tsendsuren Munkhdalai", "Xingdi Yuan", "Soroush Mehri", "Adam Trischler"], "Deep Predictive Coding Network for Object Recognition": ["Haiguang Wen", "Kuan Han", "Junxing Shi", "Yizhen Zhang", "Eugenio Culurciello", "Zhongming Liu"], "Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models": ["Raj Agrawal", "Caroline Uhler", "Tamara Broderick"], "To Understand Deep Learning We Need to Understand Kernel Learning": ["Mikhail Belkin", "Siyuan Ma", "Soumik Mandal"], "Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?": ["Zhengyuan Zhou", "Panayotis Mertikopoulos", "Nicholas Bambos", "Peter Glynn", "Yinyu Ye", "Li-Jia Li", "Li Fei-Fei"], "Mutual Information Neural Estimation": ["Mohamed Belghazi", "Aristide Baratin", "Sai Rajeswar", "Sherjil Ozair", "Yoshua Bengio", "R Devon Hjelm", "Aaron Courville"], "Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling": ["Kejun Huang", "Xiao Fu", "Nicholas Sidiropoulos"], "INSPECTRE: Privately Estimating the Unseen": ["Jayadev Acharya", "Gautam Kamath", "Ziteng Sun", "Huanyu Zhang"], "Fast Bellman Updates for Robust MDPs": ["Chin Pang Ho", "Marek Petrik", "Wolfram Wiesemann"], "Neural Dynamic Programming for Musical Self Similarity": ["Christian Walder", "Dongwoo Kim"], "Beyond the One-Step Greedy Approach in Reinforcement Learning": ["Yonathan Efroni", "Gal Dalal", "Bruno Scherrer", "Shie Mannor"], "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace": ["Yoonho Lee", "Seungjin Choi"], "Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams": ["Ashkan Norouzi-Fard", "Jakub Tarnawski", "Slobodan Mitrovic", "Amir Zandieh", "Aidasadat Mousavifar", "Ola Svensson"], "Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning": ["Ronan Fruit", "Matteo Pirotta", "Alessandro Lazaric", "Ronald Ortner"], "Variational Inference and Model Selection with Generalized Evidence Bounds": ["Liqun Chen", "Chenyang Tao", "RUIYI ZHANG", "Ricardo Henao", "Lawrence Carin"], "Constrained Interacting Submodular Groupings": ["Andrew Cotter", "Mahdi Milani Fard", "Seungil You", "Maya Gupta", "Jeff Bilmes"], "Representation Tradeoffs for Hyperbolic Embeddings": ["Frederic Sala", "Chris De Sa", "Albert Gu", "Christopher Re"], "Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima": ["Simon Du", "Jason Lee", "Yuandong Tian", "Aarti Singh", "Barnab\u00e1s P\u00f3czos"], "A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music": ["Adam Roberts", "Jesse Engel", "Colin Raffel", "Curtis Hawthorne", "Douglas Eck"], "Machine Theory of Mind": ["Neil Rabinowitz", "Frank Perbet", "Francis Song", "Chiyuan Zhang", "S. M. Ali Eslami", "Matthew Botvinick"], "Image Transformer": ["Niki Parmar", "Ashish Vaswani", "Jakob Uszkoreit", "Lukasz Kaiser", "Noam Shazeer", "Alexander Ku", "Dustin Tran"], "The Mirage of Action-Dependent Baselines in Reinforcement Learning": ["George Tucker", "Surya Bhupatiraju", "Shixiang Gu", "Richard E Turner", "Zoubin Ghahramani", "Sergey Levine"], "SQL-Rank: A Listwise Approach to Collaborative Ranking": ["LIWEI WU", "Cho-Jui Hsieh", "University of California James Sharpnack"], "Clustering Semi-Random Mixtures of Gaussians": ["Aravindan Vijayaraghavan", "Pranjal Awasthi"], "SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation": ["Bo Dai", "Albert Shaw", "Lihong Li", "Lin Xiao", "Niao He", "Zhen Liu", "Jianshu Chen", "Le Song"], "signSGD: Compressed Optimisation for Non-Convex Problems": ["Jeremy Bernstein", "Yu-Xiang Wang", "Kamyar Azizzadenesheli", "Anima Anandkumar"], "Probably Approximately Metric-Fair Learning": ["Gal Yona", "Guy Rothblum"], "Extreme Learning to Rank via Low Rank Assumption": ["Minhao Cheng", "Ian Davidson", "Cho-Jui Hsieh"], "Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation": ["Dane Corneil", "Wulfram Gerstner", "Johanni Brea"], "Asynchronous Byzantine Machine Learning (the case of SGD)": ["Georgios Damaskinos", "El Mahdi El Mhamdi", "Rachid Guerraoui", "Rhicheek Patra", "Mahsa Taziki"], "One-Shot Segmentation in Clutter": ["Claudio Michaelis", "Matthias Bethge", "Alexander Ecker"], "Improving Sign Random Projections With Additional Information": ["Keegan Kang", "Wei Pin Wong"], "Orthogonal Machine Learning: Power and Limitations": ["Ilias Zadik", "Lester Mackey", "Vasilis Syrgkanis"], "Learning Adversarially Fair and Transferable Representations": ["David Madras", "Elliot Creager", "Toniann Pitassi", "Richard Zemel"], "Learning to Explore via Meta-Policy Gradient": ["Tianbing Xu", "Qiang Liu", "Liang Zhao", "Jian Peng"], "PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos": ["Paavo Parmas", "Carl E Rasmussen", "Jan Peters", "Kenji Doya"], "GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models": ["Jiaxuan You", "Rex (Zhitao) Ying", "Xiang Ren", "Will Hamilton", "Jure Leskovec"], "Online Linear Quadratic Control": ["Alon Cohen", "Avinatan Hasidim", "Tomer Koren", "Nevena Lazic", "Yishay Mansour", "Kunal Talwar"], "The Limits of Maxing, Ranking, and Preference Learning": ["Moein Falahatgar", "Ayush Jain", "Alon Orlitsky", "Venkatadheeraj Pichapati", "Vaishakh Ravindrakumar"], "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models": ["Beilun Wang", "Arshdeep Sekhon", "Yanjun Qi"], "Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization": ["Jiong Zhang", "Qi Lei", "Inderjit Dhillon"], "Quasi-Monte Carlo Variational Inference": ["Alexander Buchholz", "Florian Wenzel", "Stephan Mandt"], "Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods": ["Junhong Lin", "Volkan Cevher"], "Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning": ["Thomas Dietterich", "George Trimponias", "Zhitang Chen"], "Accelerated Spectral Ranking": ["Arpit Agarwal", "Prathamesh Patil", "Shivani Agarwal"], "Stochastic Proximal Algorithms for AUC Maximization": ["Michael Natole Jr", "Yiming Ying", "Siwei Lyu"], "On the Spectrum of Random Features Maps of High Dimensional Data": ["Zhenyu Liao", "Romain Couillet"], "Learning Localized Spatio-Temporal Models From Streaming Data": ["Muhammad Osama", "Dave Zachariah", "Thomas Sch\u00f6n"], "Dynamic Regret of Strongly Adaptive Methods": ["Lijun Zhang", "Tianbao Yang", "rong jin", "Zhi-Hua Zhou"], "Nearly Optimal Robust Subspace Tracking": ["Praneeth Narayanamurthy", "Namrata Vaswani"], "A Semantic Loss Function for Deep Learning with Symbolic Knowledge": ["Jingyi Xu", "Zilu Zhang", "Tal Friedman", "Yitao Liang", "Guy Van den Broeck"], "Comparison-Based Random Forests": ["Siavash Haghiri", "Damien Garreau", "Ulrike von Luxburg"], "Self-Imitation Learning": ["Junhyuk Oh", "Yijie Guo", "Satinder Singh", "Honglak Lee"], "Understanding Generalization and Optimization Performance of Deep CNNs": ["Pan Zhou", "Jiashi Feng"], "Stochastic Wasserstein Barycenters": ["Sebastian Claici", "Edward Chien", "Justin Solomon"], "State Abstractions for Lifelong Reinforcement Learning": ["David Abel", "Dilip S. Arumugam", "Lucas Lehnert", "Michael L. Littman"], "Learning Diffusion using Hyperparameters": ["Dimitrios Kalimeris", "Yaron Singer", "Karthik Subbian", "Udi Weinsberg"], "Rectify Heterogeneous Models with Semantic Mapping": ["Han-Jia Ye", "De-Chuan Zhan", "Yuan Jiang", "Zhi-Hua Zhou"], "Fast Approximate Spectral Clustering for Dynamic Networks": ["Lionel Martin", "Andreas Loukas", "Pierre Vandergheynst"], "MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning": ["Bo Zhao", "Xinwei Sun", "Yanwei Fu", "Yuan Yao", "Yizhou Wang"], "Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms": ["Xueru Zhang", "Mohammad Khalili", "Mingyan Liu"], "Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?": ["Maithra Raghu", "Alexander Irpan", "Jacob Andreas", "Bobby Kleinberg", "Quoc Le", "Jon Kleinberg"], "Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis": ["Pengtao Xie", "Wei Wu", "Yichen Zhu", "Eric Xing"], "Knowledge Transfer with Jacobian Matching": ["Suraj Srinivas", "Francois Fleuret"], "Attention-based Deep Multiple Instance Learning": ["Maximilian Ilse", "Jakub Tomczak", "Max Welling"], "Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global": ["Thomas Laurent", "James von Brecht"], "TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service": ["Amartya Sanyal", "Matt Kusner", "Adria Gascon", "Varun Kanade"], "Deep Bayesian Nonparametric Tracking": ["Aonan Zhang", "John Paisley"], "Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering": ["Pan Li", "Olgica Milenkovic"], "StrassenNets: Deep Learning with a Multiplication Budget": ["Michael Tschannen", "Aran Khanna", "Animashree Anandkumar"], "Orthogonal Recurrent Neural Networks with Scaled Cayley Transform": ["Kyle Helfrich", "Devin Willmott", "Qiang Ye"], "Compiling Combinatorial Prediction Games": ["Frederic Koriche"], "Semi-Amortized Variational Autoencoders": ["Yoon Kim", "Sam Wiseman", "Andrew Miller", "David Sontag", "Alexander Rush"], "Overcoming Catastrophic Forgetting with Hard Attention to the Task": ["Joan Serr\u00e0", "Didac Suris", "Marius Miron", "Alexandros Karatzoglou"], "Not All Samples Are Created Equal: Deep Learning with Importance Sampling": ["Angelos Katharopoulos", "Francois Fleuret"], "Learning Longer-term Dependencies in RNNs with Auxiliary Losses": ["Trieu H Trinh", "Andrew Dai", "Thang Luong", "Quoc Le"], "CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions": ["Kevin Tian", "Teng Zhang", "James Zou"], "Adversarial Regression with Multiple Learners": ["Liang Tong", "Sixie Yu", "Scott Alfeld", "Yevgeniy Vorobeychik"], "Learning unknown ODE models with Gaussian processes": ["Markus Heinonen", "Cagatay Yildiz", "Henrik Mannerstr\u00f6m", "Jukka Intosalmi", "Harri L\u00e4hdesm\u00e4ki"], "Canonical Tensor Decomposition for Knowledge Base Completion": ["Timothee Lacroix", "Nicolas Usunier", "Guillaume R Obozinski"], "Celer: a Fast Solver for the Lasso with Dual Extrapolation": ["Mathurin MASSIAS", "Joseph Salmon", "Alexandre Gramfort"], "K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning": ["Jihun Hamm", "Yung-Kyun Noh"], "Learning Deep ResNet Blocks Sequentially using Boosting Theory": ["Furong Huang", "Jordan Ash", "John Langford", "Robert Schapire"], "Disentangled Sequential Autoencoder": ["Yingzhen Li", "Stephan Mandt"], "Understanding and Simplifying One-Shot Architecture Search": ["Gabriel Bender", "Pieter-Jan Kindermans", "Barret Zoph", "Vijay Vasudevan", "Quoc Le"], "Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design": ["Ahmed M. Alaa Ibrahim", "M van der Schaar"], "Deep Models of Interactions Across Sets": ["Jason Hartford", "Devon Graham", "Kevin Leyton-Brown", "Siamak Ravanbakhsh"], "Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry": ["Maximillian Nickel", "Douwe Kiela"], "Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations": ["Yiping Lu", "Aoxiao Zhong", "Quanzheng Li", "Bin Dong"], "Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering": ["Ahmed Douik", "Babak Hassibi"], "Fairness Without Demographics in Repeated Loss Minimization": ["Tatsunori Hashimoto", "Megha Srivastava", "Hongseok Namkoong", "Percy Liang"], "Stein Variational Gradient Descent Without Gradient": ["Jun Han", "Qiang Liu"], "Asynchronous Decentralized Parallel Stochastic Gradient Descent": ["Xiangru Lian", "Wei Zhang", "Ce Zhang", "Ji Liu"], "Stochastic Variance-Reduced Hamilton Monte Carlo Methods": ["Difan Zou", "Pan Xu", "Quanquan Gu"], "Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates": ["xue wang", "Mingcheng Wei", "Tao Yao"], "Adversarially Regularized Autoencoders": ["Jake Zhao", "Yoon Kim", "Kelly Zhang", "Alexander Rush", "Yann LeCun"], "Dependent Relational Gamma Process Models for Longitudinal Networks": ["Sikun Yang", "Heinz Koeppl"], "Gradient Coding from Cyclic MDS Codes and Expander Graphs": ["Netanel Raviv", "Rashish Tandon", "Alexandros Dimakis", "Itzhak Tamo"], "Dropout Training, Data-dependent Regularization, and Generalization Bounds": ["Wenlong Mou", "Yuchen Zhou", "Jun Gao", "Liwei Wang"], "Efficient Neural Audio Synthesis": ["Nal Kalchbrenner", "Erich Elsen", "Karen Simonyan", "Seb Noury", "Norman Casagrande", "Edward Lockhart", "Florian Stimberg", "A\u00e4ron van den Oord", "Sander Dieleman", "koray kavukcuoglu"], "Iterative Amortized Inference": ["Joseph Marino", "Yisong Yue", "Stephan Mandt"], "Stability and Generalization of Learning Algorithms that Converge to Global Optima": ["Zachary Charles", "Dimitris Papailiopoulos"], "Deep Variational Reinforcement Learning for POMDPs": ["Maximilian Igl", "Luisa Zintgraf", "Tuan Anh Le", "Frank Wood", "Shimon Whiteson"], "Multi-Fidelity Black-Box Optimization with Hierarchical Partitions": ["Rajat Sen", "kirthevasan kandasamy", "Sanjay Shakkottai"], "Parallel and Streaming Algorithms for K-Core Decomposition": ["Hossein Esfandiari", "Silvio Lattanzi", "Vahab Mirrokni"], "Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions": ["Wenruo Bai", "Jeff Bilmes"], "PixelSNAIL: An Improved Autoregressive Generative Model": ["Xi Chen", "Nikhil Mishra", "Mostafa Rohaninejad", "Pieter Abbeel"], "Local Private Hypothesis Testing: Chi-Square Tests": ["Marco Gaboardi", "Ryan Rogers"], "Differentiable Dynamic Programming for Structured Prediction and Attention": ["Arthur Mensch", "Mathieu Blondel"], "Black-box Adversarial Attacks with Limited Queries and Information": ["Andrew Ilyas", "Logan Engstrom", "Anish Athalye", "Jessy Lin"], "Message Passing Stein Variational Gradient Descent": ["Jingwei Zhuo", "Chang Liu", "Jiaxin Shi", "Jun Zhu", "Ning Chen", "Bo Zhang"], "Learning Compact Neural Networks with Regularization": ["Samet Oymak"], "Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings": ["John Co-Reyes", "Yu Xuan Liu", "Abhishek Gupta", "Benjamin Eysenbach", "Pieter Abbeel", "Sergey Levine"], "Kronecker Recurrent Units": ["Cijo Jose", "Mouhamadou Moustapha Cisse", "Francois Fleuret"], "Local Convergence Properties of SAGA/Prox-SVRG and Acceleration": ["Clarice Poon", "Jingwei Liang", "Carola-Bibiane Sch\u00f6nlieb"], "Scalable Bilinear Pi Learning Using State and Action Features": ["Yichen Chen", "Lihong Li", "Mengdi Wang"], "Bayesian Quadrature for Multiple Related Integrals": ["Xiaoyue Xi", "Francois-Xavier Briol", "Mark Girolami"], "Active Testing: An Efficient and Robust Framework for Estimating Accuracy": ["Phuc Nguyen", "Deva Ramanan", "Charless Fowlkes"], "Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions": ["Pan Xu", "Tianhao Wang", "Quanquan Gu"], "Selecting Representative Examples for Program Synthesis": ["Yewen Pu", "Zachery Miranda", "Armando Solar-Lezama", "Leslie Kaelbling"], "Policy and Value Transfer in Lifelong Reinforcement Learning": ["David Abel", "Yuu Jinnai", "Sophie Guo", "George Konidaris", "Michael L. Littman"], "Augment and Reduce: Stochastic Inference for Large Categorical Distributions": ["Francisco Ruiz", "Michalis Titsias", "Adji Bousso Dieng", "David Blei"], "Data-Dependent Stability of Stochastic Gradient Descent": ["Ilja Kuzborskij", "Christoph Lampert"], "Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions": ["Shuaiwen Wang", "Wenda Zhou", "Haihao Lu", "Arian Maleki", "Vahab Mirrokni"], "Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series": ["Zhengping Che", "Sanjay Purushotham", "Max Guangyu Li", "Bo Jiang", "Yan Liu"], "Neural Inverse Rendering for General Reflectance Photometric Stereo": ["Tatsunori Taniai", "Takanori Maehara"], "Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis": ["Yuxuan Wang", "Daisy Stanton", "Yu Zhang", "RJ-Skerry Ryan", "Eric Battenberg", "Joel Shor", "Ying Xiao", "Ye Jia", "Fei Ren", "Rif Saurous"], "Automatic Goal Generation for Reinforcement Learning Agents": ["Carlos Florensa", "David Held", "Xinyang Geng", "Pieter Abbeel"], "A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks": ["Akifumi Okuno", "Tetsuya Hada", "Hidetoshi Shimodaira"], "Level-Set Methods for Finite-Sum Constrained Convex Optimization": ["Qihang Lin", "Runchao Ma", "Tianbao Yang"], "Detecting and Correcting for Label Shift with Black Box Predictors": ["Zachary Lipton", "Yu-Xiang Wang", "Alexander Smola"], "Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms": ["Charlie Dickens", "Graham Cormode", "David Woodruff"], "Learning Binary Latent Variable Models: A Tensor Eigenpair Approach": ["Ariel Jaffe", "Roi Weiss", "Boaz Nadler", "Shai Carmi", "Yuval Kluger"], "A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery": ["Xiao Zhang", "Lingxiao Wang", "Yaodong Yu", "Quanquan Gu"], "First Order Generative Adversarial Networks": ["Calvin Seward", "Thomas Unterthiner", "Urs M Bergmann", "Nikolay Jetchev", "Sepp Hochreiter"], "Efficient First-Order Algorithms for Adaptive Signal Denoising": ["Dmitrii Ostrovskii", "Zaid Harchaoui"], "Coded Sparse Matrix Multiplication": ["Sinong Wang", "Jiashang Liu", "Ness Shroff"], "Learning Low-Dimensional Temporal Representations": ["Bing Su", "Ying Wu"], "Candidates vs. Noises Estimation for Large Multi-Class Classification Problem": ["Lei Han", "Yiheng Huang", "Tong Zhang"], "Bounding and Counting Linear Regions of Deep Neural Networks": ["Thiago Serra", "Christian Tjandraatmadja", "Srikumar Ramalingam"], "Inductive Two-Layer Modeling with Parametric Bregman Transfer": ["Vignesh Ganapathiraman", "Zhan Shi", "Xinhua Zhang", "Yaoliang Yu"], "Quickshift++: Provably Good Initializations for Sample-Based Mean Shift": ["Heinrich Jiang", "Jennifer Jang", "Samory Kpotufe"], "SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions": ["chandrajit bajaj", "Tingran Gao", "Zihang He", "Qixing Huang", "Zhenxiao Liang"], "Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion": ["Richard Zhang", "Salar Fattahi", "Somayeh Sojoudi"], "Parallel WaveNet: Fast High-Fidelity Speech Synthesis": ["A\u00e4ron van den Oord", "Yazhe Li", "Igor Babuschkin", "Karen Simonyan", "Oriol Vinyals", "koray kavukcuoglu", "George van den Driessche", "Edward Lockhart", "Luis C Cobo", "Florian Stimberg", "Norman Casagrande", "Dominik Grewe", "Seb Noury", "Sander Dieleman", "Erich Elsen", "Nal Kalchbrenner", "Heiga Zen", "Alex Graves", "Helen King", "Tom Walters", "Dan Belov", "Demis Hassabis"], "Path-Level Network Transformation for Efficient Architecture Search": ["Han Cai", "Jiacheng Yang", "Weinan Zhang", "Song Han", "Yong Yu"], "Subspace Embedding and Linear Regression with Orlicz Norm": ["Alexandr Andoni", "Chengyu Lin", "Ying Sheng", "Peilin Zhong", "Ruiqi Zhong"], "Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data": ["Shuai Zheng", "James Kwok"], "Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits": ["Huasen Wu", "Xueying Guo", "Xin Liu"], "Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model": ["Hideaki Imamura", "Issei Sato", "Masashi Sugiyama"], "Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)": ["Been Kim", "Martin Wattenberg", "Justin Gilmer", "Carrie Cai", "James Wexler", "Fernanda Vi\u00e9gas", "Rory sayres"], "More Robust Doubly Robust Off-policy Evaluation": ["Mehrdad Farajtabar", "Yinlam Chow", "Mohammad Ghavamzadeh"], "Decoupling Gradient-Like Learning Rules from Representations": ["Philip Thomas", "Christoph Dann", "Emma Brunskill"], "Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings": ["Aryan Mokhtari", "Hamed Hassani", "Amin Karbasi"], "Inter and Intra Topic Structure Learning with Word Embeddings": ["He Zhao", "Lan Du", "Wray Buntine", "Mingyuan Zhou"], "An Estimation and Analysis Framework for the Rasch Model": ["Andrew Lan", "Mung Chiang", "Christoph Studer"], "Minibatch Gibbs Sampling on Large Graphical Models": ["Chris De Sa", "Vincent Chen", " Wong"], "Nonconvex Optimization for Regression with Fairness Constraints": ["Junpei Komiyama", "Akiko Takeda", "Junya Honda", "Hajime Shimao"], "LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration": ["Gell\u00e9rt Weisz", "Andras Gyorgy", "Csaba Szepesvari"], "On the Relationship between Data Efficiency and Error for Uncertainty Sampling": ["Stephen Mussmann", "Percy Liang"], "Autoregressive Quantile Networks for Generative Modeling": ["Georg Ostrovski", "Will Dabney", "Remi Munos"], "The Mechanics of n-Player Differentiable Games": ["David Balduzzi", "Sebastien Racaniere", "James Martens", "Jakob Foerster", "Karl Tuyls", "Thore Graepel"], "DVAE++: Discrete Variational Autoencoders with Overlapping Transformations": ["Arash Vahdat", "William Macready", "Zhengbing Bian", "Amir Khoshaman", "Evgeny Andriyash"], "Online Convolutional Sparse Coding with Sample-Dependent Dictionary": ["Yaqing WANG", "Quanming Yao", "James Kwok", "Lionel NI"], "Stochastic Variance-Reduced Cubic Regularized Newton Method": ["Dongruo Zhou", "Pan Xu", "Quanquan Gu"], "An Efficient Semismooth Newton based Algorithm for Convex Clustering": ["Yancheng Yuan", "Defeng Sun", "Kim-Chuan Toh"], "Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data": ["Ganggang Xu", "Zuofeng Shang", "Guang Cheng"], "Solving Partial Assignment Problems using Random Clique Complexes": ["Charu Sharma", "Deepak Nathani", "Manu Kaul"], "JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets": ["Yunchen Pu", "Shuyang Dai", "Zhe Gan", "Weiyao Wang", "Guoyin Wang", "Yizhe Zhang", "Ricardo Henao", "Lawrence Carin"], "Differentially Private Identity and Equivalence Testing of Discrete Distributions": ["Maryam Aliakbarpour", "Ilias Diakonikolas", "MIT Ronitt Rubinfeld"], "Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering": ["Jan-Hendrik Lange", "Andreas Karrenbauer", "Bjoern Andres"], "Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs": ["Bin Hu", "Stephen Wright", "Laurent Lessard"], "Pathwise Derivatives Beyond the Reparameterization Trick": ["Martin Jankowiak", "Fritz Obermeyer"], "Importance Weighted Transfer of Samples in Reinforcement Learning": ["Andrea Tirinzoni", "Andrea Sessa", "Matteo Pirotta", "Marcello Restelli"], "Nonparametric variable importance using an augmented neural network with multi-task learning": ["Jean Feng", "Brian Williamson", "Noah Simon", "Marco Carone"], "Constraining the Dynamics of Deep Probabilistic Models": ["Marco Lorenzi", "Maurizio Filippone"], "Accurate Uncertainties for Deep Learning Using Calibrated Regression": ["Volodymyr Kuleshov", "Nathan Fenner", "Stefano Ermon"], "Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising": ["Borja de Balle Pigem", "Yu-Xiang Wang"], "Budgeted Experiment Design for Causal Structure Learning": ["AmirEmad Ghassami", "Saber Salehkaleybar", "Negar Kiyavash", "Elias Bareinboim"], "Blind Justice: Fairness with Encrypted Sensitive Attributes": ["Niki Kilbertus", "Adria Gascon", "Matt Kusner", "Michael Veale", "Krishna Gummadi", "Adrian Weller"], "Accurate Inference for Adaptive Linear Models": ["Yash Deshpande", "Lester Mackey", "Vasilis Syrgkanis", "Matt Taddy"], "Probabilistic Recurrent State-Space Models": ["Andreas Doerr", "Christian Daniel", "Martin Schiegg", "Duy Nguyen-Tuong", "Stefan Schaal", "Marc Toussaint", "Sebastian Trimpe"], "A Spectral Approach to Gradient Estimation for Implicit Distributions": ["Jiaxin Shi", "Shengyang Sun", "Jun Zhu"], "Alternating Randomized Block Coordinate Descent": ["Jelena Diakonikolas", "Orecchia Lorenzo"], "Learning to Optimize Combinatorial Functions": ["Nir Rosenfeld", "Eric Balkanski", "Amir Globerson", "Yaron Singer"], "Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization": ["Zeyuan Allen-Zhu"], "Learning and Memorization": ["Satrajit Chatterjee"], "The Multilinear Structure of ReLU Networks": ["Thomas Laurent", "James von Brecht"], "Does Distributionally Robust Supervised Learning Give Robust Classifiers?": ["Weihua Hu", "Gang Niu", "Issei Sato", "Masashi Sugiyama"], "A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization": ["Robin Vogel", "Aur\u00e9lien Bellet", "St\u00e9phan Cl\u00e9men\u00e7on"], "Reviving and Improving Recurrent Back-Propagation": ["Renjie Liao", "Yuwen Xiong", "Ethan Fetaya", "Lisa Zhang", "KiJung Yoon", "Zachary S Pitkow", "Raquel Urtasun", "Richard Zemel"], "An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method": ["Li Shen", "Peng Sun", "Yitong Wang", "Wei Liu", "Tong Zhang"], "Continual Reinforcement Learning with Complex Synapses": ["Christos Kaplanis", "Murray Shanahan", "Claudia Clopath"], "Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity": ["Lin Chen", "Christopher Harshaw", "Hamed Hassani", "Amin Karbasi"], "CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning": ["Wissam Siblini", "Frank Meyer", "Pascale Kuntz"], "Explicit Inductive Bias for Transfer Learning with Convolutional Networks": ["Xuhong LI", "Yves Grandvalet", "Franck Davoine"], "Improving Regression Performance with Distributional Losses": ["Ehsan Imani", "Martha White"], "Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors": ["Gintare Karolina Dziugaite", "Daniel Roy"], "LaVAN: Localized and Visible Adversarial Noise": ["Danny Karmon", "Daniel Zoran", "Yoav Goldberg"], "High Performance Zero-Memory Overhead Direct Convolutions": ["Jiyuan Zhang", "Franz Franchetti", "Tze Meng Low"], "Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control": ["Aravind Srinivas", "Allan Jabri", "Pieter Abbeel", "Sergey Levine", "Chelsea Finn"], "Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice": ["Alan Kuhnle", "J. Smith", "Victoria Crawford", "My Thai"], "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions": ["Junru Wu", "Yue Wang", "Zhenyu Wu", "Zhangyang Wang", "Ashok Veeraraghavan", "Yingyan Lin"], "Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks": ["Daphna Weinshall", "Gad A Cohen", "Dan Amir"], "Hyperbolic Entailment Cones for Learning Hierarchical Embeddings": ["Octavian-Eugen Ganea", "Gary Becigneul", "Thomas Hofmann"], "Non-linear motor control by local learning in spiking neural networks": ["Aditya Gilra", "Wulfram Gerstner"], "Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)": ["Trefor Evans", "Prasanth B Nair"], "Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning": ["Stefan Depeweg", "Jose Hernandez-Lobato", "Finale Doshi-Velez", "Steffen Udluft"], "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning": ["Yunbo Wang", "Zhifeng Gao", "Mingsheng Long", "Jianmin Wang", "Philip Yu"], "Adversarial Attack on Graph Structured Data": ["Hanjun Dai", "Hui Li", "Tian Tian", "Xin Huang", "Lin Wang", "Jun Zhu", "Le Song"], "A Boo(n) for Evaluating Architecture Performance": ["Ondrej Bajgar", "Rudolf Kadlec", "Jan Kleindienst"], "Stochastic PCA with $\\ell_2$ and $\\ell_1$ Regularization": ["Poorya Mianjy", "Raman Arora"], "GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms": ["C\u00e9dric Colas", "Olivier Sigaud", "Pierre-Yves Oudeyer"], "Neural Relational Inference for Interacting Systems": ["Thomas Kipf", "Ethan Fetaya", "Kuan-Chieh Wang", "Max Welling", "Richard Zemel"], "Junction Tree Variational Autoencoder for Molecular Graph Generation": ["Wengong Jin", "Regina Barzilay", "Tommi Jaakkola"], "Bilevel Programming for Hyperparameter Optimization and Meta-Learning": ["Luca Franceschi", "Paolo Frasconi", "Saverio Salzo", "Riccardo Grazzi", "Massimiliano Pontil"], "Towards Binary-Valued Gates for Robust LSTM Training": ["Zhuohan Li", "Di He", "Fei Tian", "Wei Chen", "Tao Qin", "Liwei Wang", "Tie-Yan Liu"], "A Progressive Batching L-BFGS Method for Machine Learning": ["Vijaya Raghavendra Bollapragada", "Jorge Nocedal", "Dheevatsa Mudigere", "Hao-Jun M Shi", "Peter Tang"], "Born Again Neural Networks": ["Tommaso Furlanello", "Zachary Lipton", "Michael Tschannen", "Laurent Itti", "Anima Anandkumar"], "Latent Space Policies for Hierarchical Reinforcement Learning": ["Tuomas Haarnoja", "Kristian Hartikainen", "Pieter Abbeel", "Sergey Levine"], "Signal and  Noise Statistics Oblivious Orthogonal Matching Pursuit": ["Sreejith Kallummil", "Sheetal Kalyani"], "End-to-End Learning for the Deep Multivariate Probit Model": ["Di Chen", "Yexiang Xue", "Carla Gomes"], "Learning the Reward Function for a Misspecified Model": ["Erik Talvitie"], "Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints": ["Ehsan Kazemi", "Morteza Zadimoghaddam", "Amin Karbasi"], "Delayed Impact of Fair Machine Learning": ["Lydia T. Liu", "Sarah Dean", "Esther Rolf", "Max Simchowitz", "University of California Moritz Hardt"], "A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming": ["Alp Yurtsever", "Olivier Fercoq", "Francesco Locatello", "Volkan Cevher"], "Firing Bandits: Optimizing Crowdfunding": ["Lalit Jain", "Kevin Jamieson"], "Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy": ["Shipra Agarwal", "Morteza Zadimoghaddam", "Vahab Mirrokni"], "QuantTree: Histograms for Change Detection in Multivariate Data Streams": ["Giacomo Boracchi", "Diego Carrera", "Cristiano Cervellera", "Danilo Macci\u00f2"], "Bandits with Delayed, Aggregated Anonymous Feedback": ["Ciara Pike-Burke", "Shipra Agrawal", "Csaba Szepesvari", "Steffen Gr\u00fcnew\u00e4lder"], "Stronger Generalization Bounds for Deep Nets via a Compression Approach": ["Sanjeev Arora", "Rong Ge", "Behnam Neyshabur", "Yi Zhang"], "Adversarial Time-to-Event Modeling": ["Paidamoyo Chapfuwa", "Chenyang Tao", "Chunyuan Li", "Courtney Page", "Benjamin Goldstein", "Lawrence Carin", "Ricardo Henao"], "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis": ["Samuel Ainsworth", "Nicholas J Foti", "Adrian KC Lee", "Emily Fox"], "Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\\ell_p$ Distances": ["Grigory Yaroslavtsev", "Adithya Vadapalli"], "Stein Variational Message Passing for Continuous Graphical Models": ["Dilin Wang", "Zhe Zeng", "Qiang Liu"], "Fair and Diverse DPP-Based Data Summarization": ["Elisa Celis", "Vijay Keswani", "Damian Straszak", "Amit Jayant Deshpande", "Tarun Kathuria", "Nisheeth Vishnoi"], "Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training": ["Xi Wu", "Wooyeong Jang", "Jiefeng Chen", "Lingjiao Chen", "Somesh Jha"], "Noisin: Unbiased Regularization for Recurrent Neural Networks": ["Adji Bousso Dieng", "Rajesh Ranganath", "Jaan Altosaar", "David Blei"], "The Weighted Kendall and High-order Kernels for Permutations": ["Yunlong Jiao", "Jean-Philippe Vert"], "Model-Level Dual Learning": ["Yingce Xia", "Xu Tan", "Fei Tian", "Tao Qin", "Nenghai Yu", "Tie-Yan Liu"], "Bayesian Uncertainty Estimation for Batch Normalized Deep Networks": ["Mattias Teye", "Hossein Azizpour", "Kevin Smith"], "RLlib: Abstractions for Distributed Reinforcement Learning": ["Eric Liang", "Richard Liaw", "Robert Nishihara", "Philipp Moritz", "Roy Fox", "Ken Goldberg", "Joseph Gonzalez", "Michael Jordan", "Ion Stoica"], "Binary Partitions with Approximate  Minimum Impurity": ["Eduardo Laber", "Marco Molinaro", "Felipe de A. Mello Pereira"]}, {"Sound Abstraction and Decomposition of Probabilistic Programs": ["Graphical Models 2"], "Graphical Nonconvex Optimization via an Adaptive Convex Relaxation": ["Optimization (Non-convex) 4"], "Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow": ["Matrix Factorization 2"], "Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms": ["Monte Carlo Methods 1"], "Active Learning with Logged Data": ["Statistical Learning Theory 5"], "Kernel Recursive ABC: Point Estimation with Intractable Likelihood": ["Kernel Methods 1"], "Adafactor: Adaptive Learning Rates with Sublinear Memory Cost": ["Deep Learning (Neural Network Architectures) 4"], "Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks": ["Deep Learning (Theory) 1"], "Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation": ["Optimization (Convex) 7"], "On Acceleration with Noise-Corrupted Gradients": ["Optimization (Convex) 4"], "Comparing Dynamics: Deep Neural Networks versus Glassy Systems": ["Deep Learning (Theory) 2"], "The Well-Tempered Lasso": ["Statistical Learning Theory 3"], "Optimization, fast and slow: optimally switching between local and Bayesian optimization": ["Optimization (Bayesian) 2"], "Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care": ["Deep Learning (Neural Network Architectures) 6"], "Communication-Computation Efficient Gradient Coding": ["Parallel and Distributed Learning 3"], "Escaping Saddles with Stochastic Gradients": ["Optimization (Non-convex) 2"], "Learning in Reproducing Kernel Kre\u0131\u0306n Spaces": ["Kernel Methods 1"], "Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data": ["Deep Learning (Adversarial) 6"], "Learning to Explain: An Information-Theoretic Perspective on Model Interpretation": ["Feature Selection 1"], "Mix & Match - Agent Curricula for Reinforcement Learning": ["Reinforcement Learning 14"], "Noise2Noise: Learning Image Restoration without Clean Data": ["Supervised Learning 1"], "Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization": ["Monte Carlo Methods 1"], "Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?": ["Optimization (Combinatorial) 1"], "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning": ["Other Applications 2"], "Analyzing Uncertainty in Neural Machine Translation": ["Natural Language and Speech Processing 2"], "Distilling the Posterior in Bayesian Neural Networks": ["Deep Learning (Bayesian) 3"], "Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing": ["Representation Learning 3"], "Towards Black-box Iterative Machine Teaching": ["Other Models and Methods 1"], "Structured Output Learning with Abstention: Application to Accurate Opinion Prediction": ["Structured Prediction 2"], "Ultra Large-Scale Feature Selection using Count-Sketches": ["Large Scale Learning and Big Data 2"], "Online Learning with Abstention": ["Online Learning 4"], "Topological mixture estimation": ["Unsupervised Learning 2"], "Linear Spectral Estimators and an Application to Phase Retrieval": ["Sparsity and Compressed Sensing 2"], "Deep One-Class Classification": ["Unsupervised Learning 1"], "End-to-end Active Object Tracking via Reinforcement Learning": ["Other Applications 1"], "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness": ["Society Impacts of Machine Learning 2"], "Practical Contextual Bandits with Regression Oracles": ["Online Learning 2"], "Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks": ["Deep Learning (Theory) 5"], "Chi-square Generative Adversarial Network": ["Generative Models 1"], "Fast Information-theoretic Bayesian Optimisation": ["Optimization (Bayesian) 2"], "Data Summarization at Scale: A Two-Stage Submodular Approach": ["Optimization (Combinatorial) 1"], "Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings": ["Supervised Learning 3"], "Measuring abstract reasoning in neural networks": ["Transfer and Multi-Task Learning 2"], "Bucket Renormalization for Approximate Inference": ["Graphical Models 1"], "Inference Suboptimality in Variational Autoencoders": ["Approximate Inference 2"], "Weightless: Lossy weight encoding for deep neural network compression": ["Other Models and Methods 2"], "Optimization Landscape and Expressivity of Deep CNNs": ["Deep Learning (Theory) 6"], "Efficient end-to-end learning for quantizable representations": ["Deep Learning (Theory) 7"], "Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors": ["Deep Learning (Bayesian) 3"], "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks": ["Transfer and Multi-Task Learning 2"], "Residual Unfairness in Fair Machine Learning from Prejudiced Data": ["Privacy, Anonymity, and Security 2"], "The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference": ["Graphical Models 2"], "Predict and Constrain: Modeling Cardinality in Deep Structured Prediction": ["Structured Prediction 1"], "An Alternative View: When Does SGD Escape Local Minima?": ["Optimization (Non-convex) 2"], "Tropical Geometry of Deep Neural Networks": ["Deep Learning (Theory) 4"], "Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order": ["Large Scale Learning and Big Data 1"], "Adversarial Learning with Local Coordinate Coding": ["Generative Models 2"], "Compressing Neural Networks using the Variational Information Bottelneck": ["Deep Learning (Neural Network Architectures) 6"], "A Spline Theory of Deep Learning": ["Deep Learning (Theory) 4"], "Semi-Supervised Learning on Data Streams via Temporal Label Propagation": ["Large Scale Learning and Big Data 2"], "Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information": ["Statistical Learning Theory 1"], "Continuous-Time Flows for Efficient Inference and Density Estimation": ["Deep Learning (Bayesian) 1"], "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam": ["Deep Learning (Bayesian) 2"], "A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations": ["Deep Learning (Theory) 8"], "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory": ["Transfer and Multi-Task Learning 1"], "Local Density Estimation in High Dimensions": ["Dimensionality Reduction 2"], "Convergence guarantees for a class of non-convex and   non-smooth optimization problems": ["Optimization (Non-convex) 5"], "RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks": ["Deep Learning (Neural Network Architectures) 2"], "Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks": ["Natural Language and Speech Processing 2"], "Visualizing and Understanding Atari Agents": ["Reinforcement Learning 9"], "Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits": ["Online Learning 1"], "SGD and Hogwild! Convergence Without the Bounded Gradients Assumption": ["Optimization (Convex) 2"], "Convergent Tree Backup and Retrace with Function Approximation": ["Reinforcement Learning 8"], "Conditional Noise-Contrastive Estimation of Unnormalised Models": ["Unsupervised Learning 1"], "Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers": ["Matrix Factorization 2"], "GAIN: Missing Data Imputation using Generative Adversarial Nets": ["Deep Learning (Adversarial) 3"], "Bounds on the Approximation Power of Feedforward Neural Networks": ["Optimization (Combinatorial) 2"], "Neural Program Synthesis from Diverse Demonstration Videos": ["Computer Vision 2"], "An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning": ["Reinforcement Learning 12"], "Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement": ["Reinforcement Learning 7"], "Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis": ["Optimization (Non-convex) 4"], "Tempered Adversarial Networks": ["Deep Learning (Adversarial) 2"], "Policy Optimization with Demonstrations": ["Reinforcement Learning 15"], "Learning Registered Point Processes from Idiosyncratic Observations": ["Time-Series Analysis 1"], "Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks": ["Parallel and Distributed Learning 2"], "Regret Minimization for Partially Observable Deep Reinforcement Learning": ["Reinforcement Learning 13"], "The Generalization Error of Dictionary Learning with Moreau Envelopes": ["Statistical Learning Theory 3"], "Towards Fast Computation of Certified Robustness for ReLU Networks": ["Deep Learning (Adversarial) 4"], "Optimizing the Latent Space of Generative Networks": ["Generative Models 2"], "DCFNet: Deep Neural Network with Decomposed Convolutional Filters": ["Deep Learning (Theory) 8"], "Smoothed Action Value Functions for Learning Gaussian Policies": ["Reinforcement Learning 10"], "Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron": ["Natural Language and Speech Processing 1"], "Constant-Time Predictive Distributions for Gaussian Processes": ["Gaussian Processes 3"], "Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control": ["Reinforcement Learning 17"], "Binary Classification with Karmic, Threshold-Quasi-Concave Metrics": ["Statistical Learning Theory 4"], "Robust and Scalable Models of Microbiome Dynamics": ["Graphical Models 1"], "Stochastic Variance-Reduced Policy Gradient": ["Reinforcement Learning 8"], "Differentiable Abstract Interpretation for Provably Robust Neural Networks": ["Deep Learning (Adversarial) 1"], "Differentially Private Matrix Completion Revisited": ["Privacy, Anonymity, and Security 1"], "Configurable Markov Decision Processes": ["Reinforcement Learning 11"], "Hierarchical Text Generation and Planning for Strategic Dialogue": ["Natural Language and Speech Processing 2"], "Conditional Neural Processes": ["Deep Learning (Neural Network Architectures) 2"], "Functional Gradient Boosting based on Residual Network Perception": ["Statistical Learning Theory 4"], "Distributed Nonparametric Regression under Communication Constraints": ["Parallel and Distributed Learning 1"], "Learning a Mixture of Two Multinomial Logits": ["Ranking and Preference Learning 1"], "Testing Sparsity over Known and Unknown Bases": ["Sparsity and Compressed Sensing 2"], "Tree Edit Distance Learning via Adaptive Symbol Embeddings": ["Representation Learning 1"], "DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding": ["Parallel and Distributed Learning 2"], "Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction": ["Computer Vision 2"], "Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks": ["Deep Learning (Theory) 6"], "Learning by Playing - Solving Sparse Reward Tasks from Scratch": ["Reinforcement Learning 4"], "State Space Gaussian Processes with Non-Gaussian Likelihood": ["Gaussian Processes 3"], "ContextNet: Deep learning for Star Galaxy Classification": ["Deep Learning (Neural Network Architectures) 10"], "Best Arm Identification in Linear Bandits with Linear Dimension Dependency": ["Reinforcement Learning 2"], "Randomized Block Cubic Newton Method": ["Optimization (Convex) 4"], "Gradually Updated Neural Networks for Large-Scale Image Recognition": ["Computer Vision 1"], "Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for  Nonconvex Distributed Optimization Over Networks": ["Optimization (Non-convex) 5"], "Is Generator Conditioning Causally Related to GAN Performance?": ["Deep Learning (Adversarial) 2"], "Semiparametric Contextual Bandits": ["Online Learning 5"], "Differentially Private Database Release via Kernel Mean Embeddings": ["Kernel Methods 1"], "Adaptive Three Operator Splitting": ["Optimization (Convex) 5"], "Learning Dynamics of Linear Denoising Autoencoders": ["Deep Learning (Theory) 5"], "Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy": ["Other Models and Methods 1"], "DiCE: The Infinitely Differentiable Monte Carlo Estimator": ["Deep Learning (Neural Network Architectures) 1"], "Differentiable plasticity: training plastic neural networks with backpropagation": ["Deep Learning (Neural Network Architectures) 1"], "Hierarchical Long-term Video Prediction without Supervision": ["Deep Learning (Neural Network Architectures) 3"], "A Unified Framework for Structured Low-rank Matrix Learning": ["Matrix Factorization 2"], "IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures": ["Reinforcement Learning 14"], "Synthesizing Programs for Images using Reinforced Adversarial Learning": ["Deep Learning (Adversarial) 5"], "The Uncertainty Bellman Equation and Exploration": ["Reinforcement Learning 17"], "Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design": ["Optimization (Bayesian) 2"], "Noisy Natural Gradient as Variational Inference": ["Deep Learning (Bayesian) 3"], "Path Consistency Learning in Tsallis Entropy Regularized MDPs": ["Reinforcement Learning 6"], "Learning Independent Causal Mechanisms": ["Representation Learning 3"], "Differentiable Compositional Kernel Learning for Gaussian Processes": ["Gaussian Processes 1"], "Analyzing the Robustness of Nearest Neighbors to Adversarial Examples": ["Statistical Learning Theory 5"], "TACO: Learning Task Decomposition via Temporal Alignment for Control": ["Deep Learning (Neural Network Architectures) 1"], "Out-of-sample extension of graph adjacency spectral embedding": ["Dimensionality Reduction 3"], "Ranking Distributions based on Noisy Sorting": ["Ranking and Preference Learning 2"], "An Inference-Based Policy Gradient Method for Learning Options": ["Reinforcement Learning 3"], "Improving Optimization in Models With Continuous Symmetry Breaking": ["Representation Learning 2"], "Kernelized Synaptic Weight Matrices": ["Deep Learning (Neural Network Architectures) 6"], "$D^2$: Decentralized Training over Decentralized Data": ["Optimization (Non-convex) 1"], "A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates": ["Optimization (Convex) 2"], "The Power of Interpolation:  Understanding the Effectiveness of SGD in Modern Over-parametrized Learning": ["Optimization (Convex) 2"], "On Nesting Monte Carlo Estimators": ["Monte Carlo Methods 2"], "Learning in Integer Latent Variable Models with Nested Automatic Differentiation": ["Graphical Models 2"], "Learning to Act in Decentralized Partially Observable MDPs": ["Multi-Agent Learning 1"], "An Iterative, Sketching-based Framework for Ridge Regression": ["Dimensionality Reduction 3"], "Generative Temporal Models with Spatial Memory for Partially Observed Environments": ["Representation Learning 3"], "Synthesizing Robust Adversarial Examples": ["Deep Learning (Adversarial) 1"], "Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations": ["Representation Learning 1"], "Recurrent Predictive State Policy Networks": ["Reinforcement Learning 13"], "Open Category Detection with PAC Guarantees": ["Other Models and Methods 1"], "On the Implicit Bias of Dropout": ["Matrix Factorization 2"], "Implicit Quantile Networks for Distributional Reinforcement Learning": ["Reinforcement Learning 1"], "Variational Bayesian dropout: pitfalls and fixes": ["Deep Learning (Bayesian) 2"], "Stagewise Safe Bayesian Optimization with Gaussian Processes": ["Optimization (Bayesian) 1"], "On Matching Pursuit and Coordinate Descent": ["Optimization (Convex) 5"], "Large-Scale Cox Process Inference using Variational Fourier Features": ["Gaussian Processes 3"], "Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces": ["Statistical Learning Theory 2"], "Semi-Implicit Variational Inference": ["Approximate Inference 1"], "Fixing a Broken ELBO": ["Deep Learning (Bayesian) 1"], "Black Box FDR": ["Feature Selection 1"], "Bayesian Optimization of Combinatorial Structures": ["Optimization (Bayesian) 1"], "Nonoverlap-Promoting Variable Selection": ["Feature Selection 1"], "Structured Evolution with Compact Architectures for Scalable Policy Optimization": ["Reinforcement Learning 2"], "Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap": ["Monte Carlo Methods 1"], "Invariance of Weight Distributions in Rectified MLPs": ["Deep Learning (Theory) 5"], "Autoregressive Convolutional Neural Networks for Asynchronous Time Series": ["Deep Learning (Neural Network Architectures) 10"], "Causal Bandits with Propagating Inference": ["Causal Inference 1"], "CRVI: Convex Relaxation for Variational Inference": ["Approximate Inference 3"], "Probabilistic Boolean Tensor Decomposition": ["Matrix Factorization 1"], "Convolutional Imputation of Matrix Networks": ["Matrix Factorization 2"], "An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks": ["Deep Learning (Theory) 2"], "Learning equations for extrapolation and control": ["Other Models and Methods 2"], "Multicalibration: Calibration for the (Computationally-Identifiable) Masses": ["Privacy, Anonymity, and Security 2"], "Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems": ["Multi-Agent Learning 1"], "A Two-Step Computation of the Exact GAN Wasserstein Distance": ["Deep Learning (Adversarial) 2"], "Learning with Abandonment": ["Reinforcement Learning 1"], "Network Global Testing by Counting Graphlets": ["Statistical Learning Theory 1"], "Learning to Reweight Examples for Robust Deep Learning": ["Supervised Learning 2"], "Learning Implicit Generative Models with the Method of Learned Moments": ["Generative Models 1"], "Learning Policy Representations in Multiagent Systems": ["Multi-Agent Learning 1"], "A Reductions Approach to Fair Classification": ["Society Impacts of Machine Learning 2"], "Safe Element Screening for Submodular Function Minimization": ["Sparsity and Compressed Sensing 1"], "Modeling Sparse Deviations for Compressed Sensing using Generative Models": ["Generative Models 5"], "Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent": ["Approximate Inference 3"], "Dimensionality-Driven Learning with Noisy Labels": ["Supervised Learning 2"], "A Classification-Based Study of Covariate Shift in GAN Distributions": ["Generative Models 1"], "Transformation Autoregressive Networks": ["Other Models and Methods 2"], "prDeep: Robust Phase Retrieval with a Flexible Deep Network": ["Optimization (Non-convex) 3"], "Thompson Sampling for Combinatorial Semi-Bandits": ["Online Learning 1"], "Hierarchical Multi-Label Classification Networks": ["Deep Learning (Neural Network Architectures) 10"], "PDE-Net: Learning PDEs from Data": ["Other Models and Methods 2"], "Modeling Others using Oneself in Multi-Agent Reinforcement Learning": ["Multi-Agent Learning 1"], "Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data": ["Gaussian Processes 1"], "Composable Planning with Attributes": ["Transfer and Multi-Task Learning 2"], "Provable Variable Selection for Streaming Features": ["Dimensionality Reduction 3"], "Approximation Guarantees for Adaptive Sampling": ["Optimization (Combinatorial) 3"], "Learning long term dependencies via Fourier recurrent units": ["Deep Learning (Neural Network Architectures) 7"], "Accelerating Greedy Coordinate Descent Methods": ["Optimization (Convex) 4"], "Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer": ["Online Learning 3"], "Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems": ["Reinforcement Learning 6"], "Coordinated Exploration in Concurrent Reinforcement Learning": ["Reinforcement Learning 2"], "Disentangling by Factorising": ["Representation Learning 3"], "Mitigating Bias in Adaptive Data Gathering via Differential Privacy": ["Privacy, Anonymity, and Security 1"], "Structured Variationally Auto-encoded Optimization": ["Gaussian Processes 2"], "Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time": ["Structured Prediction 2"], "Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization": ["Statistical Learning Theory 3"], "Efficient and Consistent Adversarial Bipartite Matching": ["Structured Prediction 1"], "Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs": ["Reinforcement Learning 1"], "Black-Box Variational Inference for Stochastic Differential Equations": ["Approximate Inference 2"], "Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches": ["Active Learning 1"], "Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices": ["Large Scale Learning and Big Data 2"], "Geometry Score: A Method For Comparing Generative Adversarial Networks": ["Generative Models 2"], "MAGAN: Aligning Biological Manifolds": ["Deep Learning (Adversarial) 5"], "Understanding the Loss Surface of Neural Networks for Binary Classification": ["Deep Learning (Theory) 3"], "Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope": ["Deep Learning (Adversarial) 1"], "Improved Training of Generative Adversarial Networks Using Representative Features": ["Deep Learning (Adversarial) 2"], "Detecting non-causal artifacts in multivariate linear regression models": ["Causal Inference 2"], "Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization": ["Parallel and Distributed Learning 2"], "Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization": ["Sparsity and Compressed Sensing 2"], "The Hierarchical Adaptive Forgetting Variational Filter": ["Causal Inference 1"], "Fast Decoding in Sequence Models Using Discrete Latent Variables": ["Deep Learning (Neural Network Architectures) 8"], "Revealing Common Statistical Behaviors in Heterogeneous Populations": ["Unsupervised Learning 2"], "Unbiased Objective Estimation in Predictive Optimization": ["Other Models and Methods 1"], "Fast Parametric Learning with Activation Memorization": ["Deep Learning (Neural Network Architectures) 4"], "Stein Points": ["Approximate Inference 3"], "Using Inherent Structures to design Lean 2-layer RBMs": ["Deep Learning (Neural Network Architectures) 9"], "SparseMAP: Differentiable Sparse Structured Inference": ["Structured Prediction 1"], "Video Prediction with Appearance and Motion Conditions": ["Computer Vision 2"], "Programmatically Interpretable Reinforcement Learning": ["Reinforcement Learning 4"], "Spline Filters For End-to-End Deep Learning": ["Deep Learning (Neural Network Architectures) 5"], "Stochastic Training of Graph Convolutional Networks with Variance Reduction": ["Networks and Relational Learning 1"], "Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework": ["Optimization (Convex) 6"], "On the Limitations of First-Order Approximation in GAN Dynamics": ["Deep Learning (Theory) 7"], "SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate": ["Other Models and Methods 1"], "Approximation Algorithms for Cascading Prediction Models": ["Optimization (Combinatorial) 4"], "Adaptive Sampled Softmax with Kernel Based Sampling": ["Natural Language and Speech Processing 2"], "Scalable approximate Bayesian inference for particle tracking data": ["Deep Learning (Bayesian) 2"], "Learning to Speed Up Structured Output Prediction": ["Structured Prediction 1"], "Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning": ["Reinforcement Learning 15"], "Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing\u2014and Back": ["Transfer and Multi-Task Learning 1"], "Let\u2019s be Honest: An Optimal No-Regret Framework for Zero-Sum Games": ["Online Learning 3"], "Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm": ["Optimization (Convex) 1"], "Feedback-Based Tree Search for Reinforcement Learning": ["Reinforcement Learning 5"], "Clipped Action Policy Gradient": ["Reinforcement Learning 16"], "Improved large-scale graph learning through ridge spectral sparsification": ["Large Scale Learning and Big Data 1"], "Progress & Compress: A scalable framework for continual learning": ["Deep Learning (Neural Network Architectures) 12"], "Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach": ["Feature Selection 1"], "High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach": ["Deep Learning (Theory) 7"], "Learning Representations and Generative Models for 3D Point Clouds": ["Generative Models 2"], "Geodesic Convolutional Shape Optimization": ["Other Applications 2"], "Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization": ["Matrix Factorization 1"], "Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression": ["Gaussian Processes 1"], "K-means clustering using random matrix sparsification": ["Clustering 1"], "Yes, but Did It Work?: Evaluating Variational Inference": ["Approximate Inference 2"], "On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups": ["Deep Learning (Theory) 8"], "BOCK : Bayesian Optimization with Cylindrical Kernels": ["Optimization (Bayesian) 1"], "Addressing Function Approximation Error in Actor-Critic Methods": ["Reinforcement Learning 10"], "Locally Private Hypothesis Testing": ["Privacy, Anonymity, and Security 1"], "Focused Hierarchical RNNs for Conditional Sequence Processing": ["Deep Learning (Neural Network Architectures) 7"], "WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models": ["Sparsity and Compressed Sensing 1"], "Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions": ["Causal Inference 1"], "Estimation of Markov Chain via Rank-constrained Likelihood": ["Optimization (Non-convex) 5"], "Accelerating Natural Gradient with Higher-Order Invariance": ["Optimization (Non-convex) 3"], "Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees": ["Optimization (Convex) 1"], "On Learning Sparsely Used Dictionaries from Incomplete Samples": ["Statistical Learning Theory 3"], "Mixed batches and symmetric discriminators for GAN training": ["Deep Learning (Adversarial) 6"], "Distributed Clustering via LSH Based Data Partitioning": ["Optimization (Combinatorial) 4"], "Training Neural Machines with Trace-Based Supervision": ["Deep Learning (Neural Network Architectures) 7"], "Fitting New Speakers Based on a Short Untranscribed Sample": ["Natural Language and Speech Processing 1"], "ADMM and Accelerated ADMM as Continuous Dynamical Systems": ["Optimization (Convex) 1"], "Neural Autoregressive Flows": ["Deep Learning (Bayesian) 3"], "Composite Marginal Likelihood Methods for Random Utility Models": ["Ranking and Preference Learning 2"], "Theoretical Analysis of Sparse Subspace Clustering with Missing Entries": ["Unsupervised Learning 2"], "Mean Field Multi-Agent Reinforcement Learning": ["Reinforcement Learning 17"], "Characterizing Implicit Bias in Terms of Optimization Geometry": ["Optimization (Convex) 3"], "Dynamic Evaluation of Neural Sequence Models": ["Deep Learning (Neural Network Architectures) 4"], "MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels": ["Supervised Learning 2"], "Anonymous Walk Embeddings": ["Representation Learning 2"], "Loss Decomposition for Fast Learning in Large Output Spaces": ["Large Scale Learning and Big Data 2"], "Representation Learning on Graphs with Jumping Knowledge Networks": ["Networks and Relational Learning 1"], "On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo": ["Monte Carlo Methods 2"], "Learning One Convolutional Layer with Overlapping Patches": ["Deep Learning (Theory) 3"], "WSNet: Compact and Efficient Networks Through Weight Sampling": ["Deep Learning (Neural Network Architectures) 13"], "Tight Regret Bounds for Bayesian Optimization in One Dimension": ["Optimization (Bayesian) 2"], "Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples": ["Deep Learning (Neural Network Architectures) 9"], "Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor": ["Reinforcement Learning 10"], "QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning": ["Multi-Agent Learning 1"], "Structured Control Nets for Deep Reinforcement Learning": ["Reinforcement Learning 3"], "Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion": ["Matrix Factorization 1"], "Temporal Poisson Square Root Graphical Models": ["Graphical Models 2"], "Do Outliers Ruin Collaboration?": ["Statistical Learning Theory 1"], "Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator": ["Reinforcement Learning 6"], "Decoupled Parallel Backpropagation with Convergence Guarantee": ["Deep Learning (Neural Network Architectures) 5"], "A Robust Approach to Sequential Information Theoretic Planning": ["Monte Carlo Methods 1"], "Efficient Gradient-Free Variational Inference using Policy Search": ["Approximate Inference 1"], "Hierarchical Imitation and Reinforcement Learning": ["Reinforcement Learning 15"], "Learning Semantic Representations for Unsupervised Domain Adaptation": ["Transfer and Multi-Task Learning 3"], "Graph Networks as Learnable Physics Engines for Inference and Control": ["Deep Learning (Neural Network Architectures) 1"], "Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines": ["Parallel and Distributed Learning 1"], "Streaming Principal Component Analysis in Noisy Setting": ["Dimensionality Reduction 1"], "Policy Optimization as Wasserstein Gradient Flows": ["Reinforcement Learning 16"], "Time Limits in Reinforcement Learning": ["Reinforcement Learning 9"], "Non-convex Conditional Gradient Sliding": ["Optimization (Non-convex) 2"], "Adversarial Risk and the Dangers of Evaluating Against Weak Attacks": ["Deep Learning (Adversarial) 1"], "Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search": ["Deep Learning (Neural Network Architectures) 3"], "CyCADA: Cycle-Consistent Adversarial Domain Adaptation": ["Transfer and Multi-Task Learning 3"], "Transfer Learning via Learning to Transfer": ["Transfer and Multi-Task Learning 1"], "Which Training Methods for GANs do actually Converge?": ["Generative Models 1"], "Theoretical Analysis of Image-to-Image Translation with Adversarial Learning": ["Generative Models 2"], "Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling": ["Reinforcement Learning 5"], "Spectrally Approximating Large Graphs with Smaller Graphs": ["Spectral Methods 1"], "Learning to Branch": ["Optimization (Combinatorial) 4"], "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples": ["Deep Learning (Adversarial) 3"], "Discovering Interpretable Representations for Both Deep Generative and Discriminative Models": ["Representation Learning 3"], "Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors": ["Online Learning 5"], "Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates": ["Statistical Learning Theory 4"], "Lipschitz Continuity in Model-based Reinforcement Learning": ["Reinforcement Learning 1"], "SADAGRAD: Strongly Adaptive Stochastic Gradient Methods": ["Optimization (Convex) 6"], "Improved nearest neighbor search using auxiliary information and priority functions": ["Unsupervised Learning 2"], "Prediction Rule Reshaping": ["Supervised Learning 1"], "The Dynamics of Learning: A Random Matrix Approach": ["Deep Learning (Theory) 1"], "BOHB: Robust and Efficient Hyperparameter Optimization at Scale": ["Optimization (Bayesian) 1"], "Variational Network Inference: Strong and Stable with Concrete Support": ["Statistical Learning Theory 1"], "Been There, Done That: Meta-Learning with Episodic Recall": ["Reinforcement Learning 7"], "Parallel Bayesian Network Structure Learning": ["Graphical Models 2"], "Crowdsourcing with Arbitrary Adversaries": ["Unsupervised Learning 1"], "A Distributed Second-Order Algorithm You Can Trust": ["Optimization (Convex) 3"], "Fourier Policy Gradients": ["Reinforcement Learning 16"], "On the Power of Over-parametrization in Neural Networks with Quadratic Activation": ["Deep Learning (Theory) 6"], "Efficient Neural Architecture Search via Parameters Sharing": ["Deep Learning (Neural Network Architectures) 5"], "Composite Functional Gradient Learning of Generative  Adversarial Models": ["Deep Learning (Adversarial) 2"], "Equivalence of Multicategory SVM and Simplex Cone SVM: Fast Computations and Statistical Theory": ["Clustering 1"], "Learning to search with MCTSnets": ["Deep Learning (Neural Network Architectures) 1"], "NetGAN: Generating Graphs via Random Walks": ["Networks and Relational Learning 2"], "Fast Variance Reduction Method with Stochastic Batch Size": ["Optimization (Convex) 2"], "Investigating Human Priors for Playing Video Games": ["Reinforcement Learning 9"], "The Hidden Vulnerability of Distributed Learning in Byzantium": ["Parallel and Distributed Learning 3"], "Bayesian Model Selection for Change Point Detection and Clustering": ["Dimensionality Reduction 3"], "Learning Steady-States of Iterative Algorithms over Graphs": ["Representation Learning 2"], "Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients": ["Optimization (Non-convex) 3"], "Shampoo: Preconditioned Stochastic Tensor Optimization": ["Optimization (Convex) 3"], "Spotlight: Optimizing Device Placement for Training Deep Neural Networks": ["Reinforcement Learning 2"], "Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization": ["Other Applications 1"], "Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations": ["Reinforcement Learning 5"], "Parameterized Algorithms for the Matrix Completion Problem": ["Ranking and Preference Learning 1"], "Classification from Pairwise Similarity and Unlabeled Data": ["Statistical Learning Theory 5"], "Tighter Variational Bounds are Not Necessarily Better": ["Deep Learning (Bayesian) 1"], "Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents": ["Reinforcement Learning 17"], "Stochastic Video Generation with a Learned Prior": ["Generative Models 4"], "Semi-Supervised Learning via Compact Latent Space Clustering": ["Deep Learning (Neural Network Architectures) 2"], "Competitive Caching with Machine Learned Advice": ["Optimization (Combinatorial) 4"], "DRACO: Byzantine-resilient Distributed Training via Redundant Gradients": ["Parallel and Distributed Learning 3"], "Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication": ["Parallel and Distributed Learning 1"], "Learning Memory Access Patterns": ["Other Applications 2"], "Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate": ["Online Learning 2"], "Hierarchical Clustering with Structural Constraints": ["Clustering 1"], "Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations": ["Deep Learning (Neural Network Architectures) 7"], "Essentially No Barriers in Neural Network Energy Landscape": ["Deep Learning (Theory) 2"], "Deep Density Destructors": ["Unsupervised Learning 1"], "Approximate message passing for amplitude based optimization": ["Optimization (Non-convex) 3"], "Gated Path Planning Networks": ["Reinforcement Learning 2"], "On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization": ["Deep Learning (Theory) 1"], "Rates of Convergence of Spectral Methods for Graphon Estimation": ["Spectral Methods 1"], "Feasible Arm Identification": ["Online Learning 1"], "Spurious Local Minima are Common in Two-Layer ReLU Neural Networks": ["Deep Learning (Theory) 6"], "Self-Bounded Prediction Suffix Tree via Approximate String Matching": ["Online Learning 3"], "Frank-Wolfe with Subsampling Oracle": ["Optimization (Convex) 5"], "Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions": ["Deep Learning (Theory) 4"], "Finding Influential Training Samples for Gradient Boosted Decision Trees": ["Supervised Learning 1"], "Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection": ["Online Learning 3"], "Deep Asymmetric Multi-task Feature Learning": ["Deep Learning (Neural Network Architectures) 9"], "Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator": ["Reinforcement Learning 16"], "Max-Mahalanobis Linear Discriminant Analysis Networks": ["Deep Learning (Adversarial) 5"], "A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning": ["Optimization (Convex) 3"], "Rapid Adaptation with Conditionally Shifted Neurons": ["Deep Learning (Neural Network Architectures) 12"], "Deep Predictive Coding Network for Object Recognition": ["Computer Vision 1"], "Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models": ["Causal Inference 2"], "To Understand Deep Learning We Need to Understand Kernel Learning": ["Kernel Methods 1"], "Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?": ["Parallel and Distributed Learning 2"], "Mutual Information Neural Estimation": ["Deep Learning (Adversarial) 6"], "Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling": ["Time-Series Analysis 1"], "INSPECTRE: Privately Estimating the Unseen": ["Privacy, Anonymity, and Security 1"], "Fast Bellman Updates for Robust MDPs": ["Reinforcement Learning 12"], "Neural Dynamic Programming for Musical Self Similarity": ["Deep Learning (Neural Network Architectures) 8"], "Beyond the One-Step Greedy Approach in Reinforcement Learning": ["Reinforcement Learning 11"], "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace": ["Deep Learning (Neural Network Architectures) 12"], "Beyond 1/2-Approximation for Submodular Maximization on Massive Data Streams": ["Optimization (Combinatorial) 1"], "Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning": ["Reinforcement Learning 6"], "Variational Inference and Model Selection with Generalized Evidence Bounds": ["Deep Learning (Bayesian) 1"], "Constrained Interacting Submodular Groupings": ["Optimization (Combinatorial) 3"], "Representation Tradeoffs for Hyperbolic Embeddings": ["Dimensionality Reduction 2"], "Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima": ["Deep Learning (Theory) 3"], "A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music": ["Deep Learning (Neural Network Architectures) 8"], "Machine Theory of Mind": ["Reinforcement Learning 7"], "Image Transformer": ["Deep Learning (Neural Network Architectures) 8"], "The Mirage of Action-Dependent Baselines in Reinforcement Learning": ["Reinforcement Learning 10"], "SQL-Rank: A Listwise Approach to Collaborative Ranking": ["Ranking and Preference Learning 2"], "Clustering Semi-Random Mixtures of Gaussians": ["Clustering 1"], "SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation": ["Reinforcement Learning 8"], "signSGD: Compressed Optimisation for Non-Convex Problems": ["Optimization (Non-convex) 1"], "Probably Approximately Metric-Fair Learning": ["Society Impacts of Machine Learning 2"], "Extreme Learning to Rank via Low Rank Assumption": ["Ranking and Preference Learning 2"], "Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation": ["Reinforcement Learning 13"], "Asynchronous Byzantine Machine Learning (the case of SGD)": ["Parallel and Distributed Learning 3"], "One-Shot Segmentation in Clutter": ["Computer Vision 1"], "Improving Sign Random Projections With Additional Information": ["Dimensionality Reduction 2"], "Orthogonal Machine Learning: Power and Limitations": ["Causal Inference 2"], "Learning Adversarially Fair and Transferable Representations": ["Transfer and Multi-Task Learning 3"], "Learning to Explore via Meta-Policy Gradient": ["Reinforcement Learning 14"], "PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos": ["Reinforcement Learning 12"], "GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models": ["Networks and Relational Learning 2"], "Online Linear Quadratic Control": ["Online Learning 5"], "The Limits of Maxing, Ranking, and Preference Learning": ["Ranking and Preference Learning 1"], "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models": ["Graphical Models 1"], "Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization": ["Deep Learning (Neural Network Architectures) 5"], "Quasi-Monte Carlo Variational Inference": ["Approximate Inference 1"], "Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods": ["Statistical Learning Theory 4"], "Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning": ["Reinforcement Learning 12"], "Accelerated Spectral Ranking": ["Ranking and Preference Learning 2"], "Stochastic Proximal Algorithms for AUC Maximization": ["Online Learning 2"], "On the Spectrum of Random Features Maps of High Dimensional Data": ["Spectral Methods 1"], "Learning Localized Spatio-Temporal Models From Streaming Data": ["Online Learning 3"], "Dynamic Regret of Strongly Adaptive Methods": ["Online Learning 4"], "Nearly Optimal Robust Subspace Tracking": ["Sparsity and Compressed Sensing 1"], "A Semantic Loss Function for Deep Learning with Symbolic Knowledge": ["Deep Learning (Neural Network Architectures) 2"], "Comparison-Based Random Forests": ["Statistical Learning Theory 5"], "Self-Imitation Learning": ["Reinforcement Learning 16"], "Understanding Generalization and Optimization Performance of Deep CNNs": ["Deep Learning (Theory) 5"], "Stochastic Wasserstein Barycenters": ["Optimization (Non-convex) 4"], "State Abstractions for Lifelong Reinforcement Learning": ["Reinforcement Learning 15"], "Learning Diffusion using Hyperparameters": ["Networks and Relational Learning 1"], "Rectify Heterogeneous Models with Semantic Mapping": ["Transfer and Multi-Task Learning 3"], "Fast Approximate Spectral Clustering for Dynamic Networks": ["Large Scale Learning and Big Data 1"], "MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning": ["Feature Selection 1"], "Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms": ["Privacy, Anonymity, and Security 2"], "Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?": ["Reinforcement Learning 9"], "Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis": ["Optimization (Convex) 7"], "Knowledge Transfer with Jacobian Matching": ["Deep Learning (Neural Network Architectures) 10"], "Attention-based Deep Multiple Instance Learning": ["Supervised Learning 3"], "Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global": ["Deep Learning (Theory) 1"], "TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service": ["Other Applications 2"], "Deep Bayesian Nonparametric Tracking": ["Time-Series Analysis 1"], "Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering": ["Spectral Methods 1"], "StrassenNets: Deep Learning with a Multiplication Budget": ["Deep Learning (Neural Network Architectures) 13"], "Orthogonal Recurrent Neural Networks with Scaled Cayley Transform": ["Deep Learning (Neural Network Architectures) 4"], "Compiling Combinatorial Prediction Games": ["Optimization (Combinatorial) 4"], "Semi-Amortized Variational Autoencoders": ["Generative Models 3"], "Overcoming Catastrophic Forgetting with Hard Attention to the Task": ["Deep Learning (Neural Network Architectures) 12"], "Not All Samples Are Created Equal: Deep Learning with Importance Sampling": ["Deep Learning (Theory) 2"], "Learning Longer-term Dependencies in RNNs with Auxiliary Losses": ["Deep Learning (Neural Network Architectures) 11"], "CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions": ["Representation Learning 1"], "Adversarial Regression with Multiple Learners": ["Privacy, Anonymity, and Security 2"], "Learning unknown ODE models with Gaussian processes": ["Gaussian Processes 2"], "Canonical Tensor Decomposition for Knowledge Base Completion": ["Networks and Relational Learning 1"], "Celer: a Fast Solver for the Lasso with Dual Extrapolation": ["Optimization (Convex) 7"], "K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning": ["Deep Learning (Adversarial) 4"], "Learning Deep ResNet Blocks Sequentially using Boosting Theory": ["Deep Learning (Theory) 2"], "Disentangled Sequential Autoencoder": ["Generative Models 4"], "Understanding and Simplifying One-Shot Architecture Search": ["Deep Learning (Neural Network Architectures) 11"], "Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design": ["Other Applications 1"], "Deep Models of Interactions Across Sets": ["Deep Learning (Neural Network Architectures) 6"], "Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry": ["Representation Learning 1"], "Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations": ["Deep Learning (Neural Network Architectures) 9"], "Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering": ["Optimization (Non-convex) 4"], "Fairness Without Demographics in Repeated Loss Minimization": ["Society Impacts of Machine Learning 1"], "Stein Variational Gradient Descent Without Gradient": ["Monte Carlo Methods 2"], "Asynchronous Decentralized Parallel Stochastic Gradient Descent": ["Optimization (Non-convex) 1"], "Stochastic Variance-Reduced Hamilton Monte Carlo Methods": ["Monte Carlo Methods 1"], "Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates": ["Online Learning 5"], "Adversarially Regularized Autoencoders": ["Deep Learning (Adversarial) 6"], "Dependent Relational Gamma Process Models for Longitudinal Networks": ["Networks and Relational Learning 2"], "Gradient Coding from Cyclic MDS Codes and Expander Graphs": ["Optimization (Convex) 3"], "Dropout Training, Data-dependent Regularization, and Generalization Bounds": ["Statistical Learning Theory 2"], "Efficient Neural Audio Synthesis": ["Deep Learning (Neural Network Architectures) 11"], "Iterative Amortized Inference": ["Generative Models 3"], "Stability and Generalization of Learning Algorithms that Converge to Global Optima": ["Statistical Learning Theory 2"], "Deep Variational Reinforcement Learning for POMDPs": ["Reinforcement Learning 13"], "Multi-Fidelity Black-Box Optimization with Hierarchical Partitions": ["Online Learning 4"], "Parallel and Streaming Algorithms for K-Core Decomposition": ["Large Scale Learning and Big Data 1"], "Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions": ["Optimization (Combinatorial) 3"], "PixelSNAIL: An Improved Autoregressive Generative Model": ["Deep Learning (Neural Network Architectures) 8"], "Local Private Hypothesis Testing: Chi-Square Tests": ["Privacy, Anonymity, and Security 1"], "Differentiable Dynamic Programming for Structured Prediction and Attention": ["Structured Prediction 2"], "Black-box Adversarial Attacks with Limited Queries and Information": ["Deep Learning (Adversarial) 3"], "Message Passing Stein Variational Gradient Descent": ["Approximate Inference 3"], "Learning Compact Neural Networks with Regularization": ["Optimization (Non-convex) 4"], "Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings": ["Reinforcement Learning 3"], "Kronecker Recurrent Units": ["Deep Learning (Neural Network Architectures) 4"], "Local Convergence Properties of SAGA/Prox-SVRG and Acceleration": ["Optimization (Convex) 6"], "Scalable Bilinear Pi Learning Using State and Action Features": ["Reinforcement Learning 8"], "Bayesian Quadrature for Multiple Related Integrals": ["Gaussian Processes 1"], "Active Testing: An Efficient and Robust Framework for Estimating Accuracy": ["Computer Vision 1"], "Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions": ["Optimization (Convex) 6"], "Selecting Representative Examples for Program Synthesis": ["Active Learning 1"], "Policy and Value Transfer in Lifelong Reinforcement Learning": ["Reinforcement Learning 11"], "Augment and Reduce: Stochastic Inference for Large Categorical Distributions": ["Approximate Inference 2"], "Data-Dependent Stability of Stochastic Gradient Descent": ["Statistical Learning Theory 2"], "Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions": ["Large Scale Learning and Big Data 2"], "Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series": ["Generative Models 5"], "Neural Inverse Rendering for General Reflectance Photometric Stereo": ["Computer Vision 1"], "Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis": ["Natural Language and Speech Processing 1"], "Automatic Goal Generation for Reinforcement Learning Agents": ["Reinforcement Learning 4"], "A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks": ["Representation Learning 2"], "Level-Set Methods for Finite-Sum Constrained Convex Optimization": ["Optimization (Convex) 6"], "Detecting and Correcting for Label Shift with Black Box Predictors": ["Transfer and Multi-Task Learning 3"], "Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms": ["Dimensionality Reduction 1"], "Learning Binary Latent Variable Models: A Tensor Eigenpair Approach": ["Matrix Factorization 1"], "A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery": ["Matrix Factorization 1"], "First Order Generative Adversarial Networks": ["Deep Learning (Adversarial) 4"], "Efficient First-Order Algorithms for Adaptive Signal Denoising": ["Optimization (Convex) 7"], "Coded Sparse Matrix Multiplication": ["Parallel and Distributed Learning 1"], "Learning Low-Dimensional Temporal Representations": ["Dimensionality Reduction 3"], "Candidates vs. Noises Estimation for Large Multi-Class Classification Problem": ["Supervised Learning 3"], "Bounding and Counting Linear Regions of Deep Neural Networks": ["Deep Learning (Theory) 8"], "Inductive Two-Layer Modeling with Parametric Bregman Transfer": ["Supervised Learning 1"], "Quickshift++: Provably Good Initializations for Sample-Based Mean Shift": ["Clustering 1"], "SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions": ["Spectral Methods 1"], "Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion": ["Graphical Models 1"], "Parallel WaveNet: Fast High-Fidelity Speech Synthesis": ["Generative Models 4"], "Path-Level Network Transformation for Efficient Architecture Search": ["Deep Learning (Neural Network Architectures) 11"], "Subspace Embedding and Linear Regression with Orlicz Norm": ["Dimensionality Reduction 1"], "Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data": ["Optimization (Convex) 2"], "Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits": ["Online Learning 4"], "Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model": ["Unsupervised Learning 1"], "Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)": ["Other Models and Methods 2"], "More Robust Doubly Robust Off-policy Evaluation": ["Reinforcement Learning 1"], "Decoupling Gradient-Like Learning Rules from Representations": ["Reinforcement Learning 12"], "Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings": ["Optimization (Combinatorial) 3"], "Inter and Intra Topic Structure Learning with Word Embeddings": ["Generative Models 5"], "An Estimation and Analysis Framework for the Rasch Model": ["Other Applications 1"], "Minibatch Gibbs Sampling on Large Graphical Models": ["Monte Carlo Methods 2"], "Nonconvex Optimization for Regression with Fairness Constraints": ["Society Impacts of Machine Learning 1"], "LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration": ["Statistical Learning Theory 1"], "On the Relationship between Data Efficiency and Error for Uncertainty Sampling": ["Active Learning 1"], "Autoregressive Quantile Networks for Generative Modeling": ["Generative Models 4"], "The Mechanics of n-Player Differentiable Games": ["Deep Learning (Adversarial) 4"], "DVAE++: Discrete Variational Autoencoders with Overlapping Transformations": ["Generative Models 3"], "Online Convolutional Sparse Coding with Sample-Dependent Dictionary": ["Sparsity and Compressed Sensing 1"], "Stochastic Variance-Reduced Cubic Regularized Newton Method": ["Optimization (Non-convex) 2"], "An Efficient Semismooth Newton based Algorithm for Convex Clustering": ["Optimization (Convex) 1"], "Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data": ["Parallel and Distributed Learning 1"], "Solving Partial Assignment Problems using Random Clique Complexes": ["Computer Vision 2"], "JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets": ["Deep Learning (Adversarial) 6"], "Differentially Private Identity and Equivalence Testing of Discrete Distributions": ["Statistical Learning Theory 3"], "Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering": ["Optimization (Combinatorial) 2"], "Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs": ["Optimization (Convex) 1"], "Pathwise Derivatives Beyond the Reparameterization Trick": ["Approximate Inference 3"], "Importance Weighted Transfer of Samples in Reinforcement Learning": ["Reinforcement Learning 11"], "Nonparametric variable importance using an augmented neural network with multi-task learning": ["Deep Learning (Neural Network Architectures) 10"], "Constraining the Dynamics of Deep Probabilistic Models": ["Gaussian Processes 2"], "Accurate Uncertainties for Deep Learning Using Calibrated Regression": ["Deep Learning (Bayesian) 2"], "Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising": ["Privacy, Anonymity, and Security 2"], "Budgeted Experiment Design for Causal Structure Learning": ["Causal Inference 1"], "Blind Justice: Fairness with Encrypted Sensitive Attributes": ["Society Impacts of Machine Learning 2"], "Accurate Inference for Adaptive Linear Models": ["Causal Inference 2"], "Probabilistic Recurrent State-Space Models": ["Gaussian Processes 2"], "A Spectral Approach to Gradient Estimation for Implicit Distributions": ["Approximate Inference 1"], "Alternating Randomized Block Coordinate Descent": ["Optimization (Convex) 4"], "Learning to Optimize Combinatorial Functions": ["Optimization (Combinatorial) 2"], "Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization": ["Optimization (Non-convex) 1"], "Learning and Memorization": ["Supervised Learning 3"], "The Multilinear Structure of ReLU Networks": ["Deep Learning (Theory) 3"], "Does Distributionally Robust Supervised Learning Give Robust Classifiers?": ["Supervised Learning 1"], "A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization": ["Statistical Learning Theory 5"], "Reviving and Improving Recurrent Back-Propagation": ["Deep Learning (Theory) 5"], "An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method": ["Optimization (Convex) 7"], "Continual Reinforcement Learning with Complex Synapses": ["Reinforcement Learning 7"], "Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity": ["Online Learning 2"], "CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning": ["Supervised Learning 3"], "Explicit Inductive Bias for Transfer Learning with Convolutional Networks": ["Transfer and Multi-Task Learning 2"], "Improving Regression Performance with Distributional Losses": ["Supervised Learning 2"], "Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors": ["Deep Learning (Theory) 7"], "LaVAN: Localized and Visible Adversarial Noise": ["Deep Learning (Adversarial) 4"], "High Performance Zero-Memory Overhead Direct Convolutions": ["Deep Learning (Neural Network Architectures) 9"], "Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control": ["Reinforcement Learning 4"], "Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice": ["Optimization (Combinatorial) 3"], "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions": ["Deep Learning (Neural Network Architectures) 13"], "Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks": ["Supervised Learning 2"], "Hyperbolic Entailment Cones for Learning Hierarchical Embeddings": ["Representation Learning 1"], "Non-linear motor control by local learning in spiking neural networks": ["Deep Learning (Neural Network Architectures) 3"], "Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)": ["Gaussian Processes 3"], "Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning": ["Deep Learning (Bayesian) 2"], "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning": ["Deep Learning (Neural Network Architectures) 3"], "Adversarial Attack on Graph Structured Data": ["Deep Learning (Adversarial) 3"], "A Boo(n) for Evaluating Architecture Performance": ["Deep Learning (Theory) 7"], "Stochastic PCA with $\\ell_2$ and $\\ell_1$ Regularization": ["Dimensionality Reduction 1"], "GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms": ["Reinforcement Learning 9"], "Neural Relational Inference for Interacting Systems": ["Networks and Relational Learning 2"], "Junction Tree Variational Autoencoder for Molecular Graph Generation": ["Generative Models 3"], "Bilevel Programming for Hyperparameter Optimization and Meta-Learning": ["Transfer and Multi-Task Learning 1"], "Towards Binary-Valued Gates for Robust LSTM Training": ["Natural Language and Speech Processing 1"], "A Progressive Batching L-BFGS Method for Machine Learning": ["Optimization (Non-convex) 5"], "Born Again Neural Networks": ["Deep Learning (Neural Network Architectures) 13"], "Latent Space Policies for Hierarchical Reinforcement Learning": ["Reinforcement Learning 3"], "Signal and  Noise Statistics Oblivious Orthogonal Matching Pursuit": ["Sparsity and Compressed Sensing 2"], "End-to-End Learning for the Deep Multivariate Probit Model": ["Structured Prediction 2"], "Learning the Reward Function for a Misspecified Model": ["Reinforcement Learning 5"], "Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints": ["Optimization (Combinatorial) 1"], "Delayed Impact of Fair Machine Learning": ["Society Impacts of Machine Learning 1"], "A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming": ["Optimization (Convex) 5"], "Firing Bandits: Optimizing Crowdfunding": ["Online Learning 4"], "Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy": ["Optimization (Combinatorial) 2"], "QuantTree: Histograms for Change Detection in Multivariate Data Streams": ["Unsupervised Learning 2"], "Bandits with Delayed, Aggregated Anonymous Feedback": ["Online Learning 1"], "Stronger Generalization Bounds for Deep Nets via a Compression Approach": ["Deep Learning (Theory) 4"], "Adversarial Time-to-Event Modeling": ["Deep Learning (Adversarial) 5"], "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis": ["Generative Models 5"], "Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\\ell_p$ Distances": ["Dimensionality Reduction 2"], "Stein Variational Message Passing for Continuous Graphical Models": ["Graphical Models 1"], "Fair and Diverse DPP-Based Data Summarization": ["Society Impacts of Machine Learning 1"], "Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training": ["Deep Learning (Adversarial) 5"], "Noisin: Unbiased Regularization for Recurrent Neural Networks": ["Generative Models 5"], "The Weighted Kendall and High-order Kernels for Permutations": ["Ranking and Preference Learning 1"], "Model-Level Dual Learning": ["Deep Learning (Neural Network Architectures) 3"], "Bayesian Uncertainty Estimation for Batch Normalized Deep Networks": ["Deep Learning (Bayesian) 3"], "RLlib: Abstractions for Distributed Reinforcement Learning": ["Reinforcement Learning 14"], "Binary Partitions with Approximate  Minimum Impurity": ["Optimization (Combinatorial) 2"]}, {"Franck Davoine": "CNRS, Universit\u00e9 de technologie de Compi\u00e8gne", "Marco Lorenzi": "Inria Sophia Antipolis", "An Bian": "ETH Zurich", "Jingyi Xu": "University of California, Los Angeles", "Jaakko Lehtinen": "Aalto University & NVIDIA", "George Trimponias": "Huawei Noah's Ark Lab", "Samory Kpotufe": "Princeton University", "Theo Damoulas": "University of Warwick", "Fred Roosta": "University of Queensland", "Lan Du": "Faculty of Information Technology, Monash University", "Krzysztof Choromanski": "Google Brain Robotics", "Jeff Schneider": "Uber/CMU", "Carla Gomes": "Cornell University", "Satinder Singh": "University of Michigan", "Diego Carrera": "Politecnico di Milano", "Yori Zwols": "DeepMind", "Andrea Sessa": "Politecnico di Milano", "Matteo Hessel": "Deep Mind", "Ying WEI": "Tencent AI Lab", "Mengye Ren": "Uber ATG / University of Toronto", "Augustin Zidek": "", "Saleh Nabi": "", "Sanjeev Arora": " Princeton University and Institute for Advanced Study", "Wei Wu": "Carnegie Mellon University", "Devendra Singh Chaplot": "Carnegie Mellon University", "Alexander Grigorevskiy": "Aalto University", "Pushmeet Kohli": "DeepMind", "Shixiang Gu": "Cambridge", "Yang Song": "Stanford University", "Elad Hazan": "Google Brain and Princeton University", "Timothy Verstraeten": "Vrije Universiteit Brussel", "Adam Klivans": "University of Texas at Austin", " Wong": "Stanford university", "Songbai Yan": "University of California San Diego", "Manfred Salmhofer": "Heidelberg University", "Yuan Yao": "Hong Kong Science Tech", "David Silver": "Google DeepMind", "Martin Riedmiller": "DeepMind", "Adithya Vadapalli": "INDIANA UNIVERSITY", "Abhinav Anand": "Indian Institute of Science", "Takafumi Kajihara": "NEC", "Alexander Buchholz": "ENSAE-CREST Paris", "Andrea Zanette": "Stanford University", "Geoff Pleiss": "Cornell University", "Lin Chen": "Yale University", "Di Chen": "Cornell University", "Thomas Kipf": "University of Amsterdam", "Maria Dimakopoulou": "Stanford", "Evgeny Burnaev": "Skoltech", "Zachery Miranda": "MIT", "Yunseok Jang": "Seoul National University", "Lars Mescheder": "MPI T\u00fcbingen", "Yee Whye Teh": "Oxford and DeepMind", "Yichi Zhou": "Tsinghua University", "Jacob Munkberg": "NVIDIA", "Arthur Szlam": "Facebook", "Marcello Restelli": "Politecnico di Milano", "Beilun Wang": "University of Virginia", "Chris Maddison": "University of Oxford", "Iain Dunning": "", "David Madras": "University of Toronto", "Michael Cohen": "", "Yuandong Tian": "Facebook AI Research", "Yao Ma": "Boston University", "Elisa Celis": "EPFL", "Xiaoyue Xi": "Imperial College London", "Ilya Tolstikhin": "Max Planck Institute for Intelligent Systems, T\u00fcbingen", "Gunnar Raetsch": "ETH Zurich", "Roland Hafner": "DeepMind", "Soroush Mehri": "Microsoft Research", "Jianshu Chen": "Microsoft Research", "Stephen McGough": "Newcastle University", "Tom Rainforth": "University of Oxford", "Clarice Poon": "University of Cambridge", "Douglas Eck": "Google Brain", "Jiasen Yang": "Purdue University", "Di He": "Peking University", "Han Cai": "Shanghai Jiao Tong University", "Lam Nguyen": "Lehigh University & IBM T.J. Watson Research Center", "Inderjit Dhillon": "UT Austin & Amazon", "Ricardo Baptista": "Massachusetts Institute of Technology", "Rene Vidal": "Johns Hopkins University", "Ujjwal Jain": "IIT Bombay", "Changhao Yan": "", "Georg Martius": "Max Planck Institute for Intelligent Systems", "Jayadev Acharya": "Cornell University", "Agnieszka Grabska-Barwinska": "DeepMind", "Erich Elsen": "", "Jose Hernandez-Lobato": "University of Cambridge", "Haitao Liu": "Rolls-Royce@NTU Corp Lab", "Tara Javidi": "University of California San Diego", "Moses Charikar": "Stanford University", "Thanh Huy Nguyen": "Telecom ParisTech", "Christoph Studer": "Cornell University", "Deepak Pathak": "UC Berkeley", "Teng Zhang": "Stanford University", "Russ Salakhutdinov": "Carnegie Mellen University", "Claudio Gallicchio": "University of Pisa", "Joseph Lim": "Univ. of Southern California", "Bo Zhao": "Peking University", "Jonathan Uesato": "DeepMind", "Qixing Huang": "The University of Texas at Austin", "David J. Mack": "University Hospital Zurich", "Voot Tangkaratt": "RIKEN AIP", "Anurag Koul": "Oregon State University", "Kelly Zhang": "New York University", "Yishay Mansour": "Google", "Paul Vicol": "University of Toronto", "Hannes Nickisch": "Philips Research", "Daphna Weinshall": "Hebrew University of Jerusalem, Israel", "Eduardo Laber": "PUC-RIO", "Ruoyu Sun": "University of Illinois at Urbana-Champaign", "Gautier Marti": "Ecole Polytechnique AXA IM Chorus", "Junru Wu": "Texas A&M University", "Francois Fleuret": "Idiap research institute", "Yanwei Fu": "Fudan university", "Jason Hartford": "University of British Columbia", "Tal Wagner": "MIT", "Maya Gupta": "Google", "Raia Hadsell": "DeepMind", "Soumya Ghosh": "IBM Research", "Jan-Hendrik Lange": "Max Planck Institute for Informatics", "Cheng Deng": "Xidian University", "Aurelien Lucchi": "ETH Zurich", "Alexandre Gramfort": "Inria", "Yang Yuan": "Cornell University", "Jerry Li": "MIT", "Jeffrey Pennington": "Google Brain", "Yotam Doron": "DeepMind", "Mingzhang Yin": "University of Texas at Austin", "Hiroyuki Sato": "Kyoto University", "Alex Irpan": "Google", "Joan Serr\u00e0": "Telef\u00f3nica Research, Barcelona", "Lucas Lehnert": "Brown University", "James Kwok": "Hong Kong University of Science and Technology", "Abhradeep Thakurta": "UCSC", "Quynh Nguyen": "Saarland University", "Eric Liang": "University of California, Berkeley", "Siddharth Barman": "Indian Institute of Science", "Maryam Aliakbarpour": "MIT", "Zachary Charles": "University of Wisconsin-Madison", "Alex Ihler": "UC Irvine", "Jascha Sohl-Dickstein": "Google Brain", "Alina Beygelzimer": "Yahoo Research", "Andrew Golightly": "Newcastle University", "Mi Zhang": "Fudan University", "Mihaela van der Schaar": "University of Oxford", "Motonobu Kanagawa": "Max Planck Institute for Intelligent Systems", "Joseph Salmon": "Telecom ParisTech", "Seungjin Choi": "POSTECH", "Heinz Koeppl": "TU Darmstadt", "Vinayak A Rao": "Purdue University", "Takayuki Okatani": 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"Stanford University", "Charless Fowlkes": "UC Irvine", "Thomas Miconi": "Uber AI Labs", "Federico Errica": "University of Pisa", "Yaron Singer": "Harvard", "Varun Kanade": "University of Oxford", "Damian Straszak": "EPFL", "Michalis Titsias": "Athens University of Economics and Business", "Aida Mousavifar": "EPFL", "Siwei Lyu": "University at Albany, State University of New York", "Maximillian Nickel": "Facebook AI Research", "Matt Kusner": "Alan Turing Institute", "Thomas Sch\u00f6n": "Uppsala University", "Ankit Patel": "Rice University, Baylor College of Medicine", "David Lopez-Paz": "Facebook AI Research", "Peter Dayan": "UCL", "Kenji Fukumizu": "Institute of Statistical Mathematics", "Dipendra Misra": "Cornell University", "Udit Gupta": "Harvard University", "David Brooks": "Harvard University", "Alex Aiken": "Stanford University", "Prof. Darrell": "University of California at Berkeley", "Min Ye": "Princeton University", "Jure Leskovec": "Stanford University", "Daniel Nikovski": "Mitsubishi Electric Research Labs", "Zhuohan Li": "Peking University", "Tuomas Sandholm": "Carnegie Mellon University", "Matthias Bethge": "University of T\u00fcbingen", "Tabish Rashid": "University of Oxford", "Shao-Hua Sun": "University of Southern California", "Ryan Spring": "Rice University", "De-Chuan Zhan": "Nanjing University", "Shoaib Ahmed Siddiqui": "German Research Center for Artificial Intelligence", "Li Shen": "Tencent AI Lab", "Alekh Agarwal": "Microsoft Research", "Quanzheng Li": "Mass General Hospital, Harvard Medical School", "Negar Kiyavash": "University of Illinois at Urbana-Champaign", "Tim Pearce": "University of Cambridge", "Hao-Jun M Shi": "Northwestern University", "Noam Shazeer": "Google", "Yingce Xia": "University of Science and Technology of China", "Poorya Mianjy": "Johns Hopkins University", "Prasanth B Nair": "University of Toronto", "Raj Agrawal": "MIT", "Lin Yang": "Princeton", "Surya Bhupatiraju": "Google Brain", "Liqun Chen": "Duke University", "Hyeonwoo Noh": "POSTECH", "Liang Zhao": "Baidu Research USA", "Ibrahim Alabdulmohsin": "Saudi Aramco", "Samy Bengio": "Google Brain", "Yizhen Wang": "UCSD", "David Balduzzi": "DeepMind", "Babak Hassibi": "Caltech", "Xinyang Geng": "UC Berkeley", "Yann LeCun": "New York University", "Deepak Nathani": "IIT Hyderabad", "Ethan Fetaya": "University of Toronto", "Yizhou Sun": "UCLA", "Jennifer Jang": "Uber", "Andras Gyorgy": "DeepMind", "Vlad Niculae": "Cornell University", "David Saxton": "DeepMind", "Rob Clark": "Google UK", "Davide Bacciu": "University of Pisa", "Shusen Wang": "UC Berkeley", "Om Thakkar": "Boston University", "James Bailey": "The University of Melbourne", "Logan Engstrom": "MIT", "Aleksander Madry": "MIT", "Didac Suris": "Universitat Politecnica de Catalunya", "Zhihao Jia": "Stanford University", "Moein Falahatgar": "UC San Diego", "Ya-Ping Hsieh": "\u00c9cole Polytechnique F\u00e9d\u00e9rale d", "Walter Karlen": "ETH Zurich", "Tamer Basar": "", "Michal Valko": "Inria Lille - Nord Europe", "Aryan Mokhtari": "MIT", "Shin-ichi Maeda": "Preferred Networks, Inc.", "Steffen Gr\u00fcnew\u00e4lder": "Lancaster University", "Loic Le Folgoc": "Imperial College London", "Weihua Hu": "The University of Tokyo", "Dustin Tran": "Google", "Daniel Z\u00fcgner": "Technical University of Munich", "Been Kim": "Google", "Aurick Zhou": "UC Berkeley", "Ludwig Schmidt": "MIT", "Alexander Pritzel": "Deepmind", "Sinong Wang": "The Ohio State University", "Sudipto Guha": "Amazon", "Xiao Fu": "Oregon State University", "Christopher Re": "Stanford", "Remi Munos": "DeepMind", "Nicholas Hay": "", "Adam Roberts": "Google Brain", "Zhaoran Wang": "Northwestern U", "Felix Draxler": "Heidelberg University", "Eunho Yang": "KAIST / AItrics", "Eric Tzeng": "UC Berkeley", "Yaoliang Yu": "University of Waterloo", "Nisheeth Vishnoi": "EPFL", "Adam Polyak": "Facebook AI Research and Tel Aviv University", "Andreas Loukas": "EPFL", "Ying Xiao": "Google Inc", "Udi Weinsberg": "Facebook", "Damien Garreau": "Max Planck Institute", "Lingxiao Wang": "University of Virginia", "Maryam Fazel": "University of Washington", "Hugo Raguet": "LIVE (CNRS)", "othmane mazhar": "Royal Institute of Technology", "Kevin Kwok": "LabSix", "Samuel Greydanus": "Oregon State University", "Dhruv Malik": "UC Berkeley", "Sebastian Trimpe": "Max Planck Institute for Intelligent Systems", "Nir Rosenfeld": "Harvard University", "Peter Richtarik": "King Abdullah University of Science and Technology (KAUST) - University of Edinburgh, Scotland", "Shane Legg": "DeepMind", "Fritz Obermeyer": "Uber AI Labs", "EECS Anca Dragan": "EECS Department, University of California, Berkeley", "Florian Stimberg": "", "Peter Bartlett": "UC Berkeley", "Lihong Li": "Google Inc.", "Hongyi Wang": "University of Wisconsin-Madison", "Massimiliano Pontil": "University College London", "Zhishuai Zhang": "Johns Hopkins University", "Megha Srivastava": "Stanford University", "Philippe Donnat": "Hellebore Capital Limited", "Richard Baraniuk": "OpenStax / Rice University", "Melody Guan": "Stanford University", "Baoxiong Jia": "Peking University", "Jakub Tarnawski": "EPFL", "Ahmed Touati": "MILA", "Chinmay Hegde": "Iowa State University", "Oriol Vinyals": "DeepMind", "Andreas Karrenbauer": "Max Planck Institute for Informatics", "Tero Karras": "NVIDIA", "Phil Long": "Google", "Pan Zhou": "National University of Singapore", "Bruno Scherrer": "INRIA", "Jonas Kohler": "ETH Zurich", "Masashi Sugiyama": "RIKEN / The University of Tokyo", "Jacob Andreas": "UC Berkeley", "Song Han": "MIT", "Harrison Edwards": "OpenAI / University of Edinburgh", "Nicholas Bambos": "", "Zaid Harchaoui": "University of Washington", "IEMS Xingyu Wang": "IEMS, Northwestern University", "Aur\u00e9lien Bellet": "INRIA", "Ciwan Ceylan": "RWTH", "Emily Denton": "New York University", "Yiheng Huang": "Tencent AI Lab", "Vijay Keswani": "EPFL", "Yuxuan Wang": "Google", "Aleksandar Bojchevski": "Technical University of Munich", "Peter Glynn": "Stanford University", "James Lucas": "University of Toronto", "Sarah Erfani": "University of Melbourne", "Adrian KC Lee": "University of Washington", "Heng Huang": "University of Pittsburgh", "Yunchen Pu": "Duke", "Peter Battaglia": "DeepMind", "Lawrence Carin": "Duke", "Asish Ghoshal": "Purdue University", "Marc Toussaint": "(organization)", "Stefano Spigler": "", "Edward Lockhart": "", "Mario Srouji": "Carnegie Mellon University", "Felipe de A. Mello Pereira": "PUC-Rio", "Hui Qian": "Zhejiang University", "Trieu H Trinh": "Google Brain", "Heiner Litz": "UC Santa Cruz", "Noble Kennamer": "University of California, Irvine", "Bin Yang": "Uber ATG / University of Toronto", "Petros Drineas": "Purdue University", "Jiashun Jin": "Carnegie Mellon University", "Hyunjik Kim": "DeepMind, University of Oxford", "Scott Fujimoto": "McGill University", "Andy Neely": "", "Vaishakh Ravindrakumar": "UC San Diego", "Liwen Zhang": "University of Chicago", "Zebang Shen": "Zhejiang University", "Mostafa Rohaninejad": "", "Nataly Brukhim": "Tel Aviv University", "Venkatadheeraj Pichapati": "University of California San Diego", "Thomas Laurent": "Loyola Marymount University", "Didrik Nielsen": "RIKEN", "Guillermo Sapiro": "Duke University", "Tim Rockt\u00e4schel": "University of Oxford", "Richard Nock": "Data61, The Australian National University and the University of Sydney", "Jianfei Cai": "Nanyang Technological University", "RUIYI ZHANG": "Duke University", "Baining Guo": "MSR Asia", "Xi Wu": "Google", "Wesley Tansey": "Columbia University", "Siamak Ravanbakhsh": "University of British Columbia", "Nathan Kallus": "Cornell University", "Anant Raj": "Max-Planck Institute for Intelligent Systems", "Jennifer Neville": "Purdue University", "Anru Zhang": "University of Wisconsin-Madison", "Yu Zhang": "Google", "Aki Vehtari": "Aalto University", "Sasha Salter": "University of Oxford", "Chris Harshaw": "Yale University", "Jessy Lin": "MIT", "Phil Schniter": "Ohio State", "Tammo Rukat": "University of Oxford", "Chen Zhu": "ShanghaiTech University", "Moran Feldman": "The Open University of Israel", "Matthew Botvinick": "DeepMind", "Elliot Meyerson": "UT Austin - Sentient Technologies", "Kavosh Asadi": "Brown University", "Pierre Baque": "EPFL", "Chengyu Lin": "Columbia University", "David Woodruff": "Carnegie Mellon University", "Xiaoxuan Zhang": "University of Iowa", "Akiko Takeda": "The Institute of Statistical Mathematics", "Rishabh Singh": "Google Brain", "Claudio Gentile": "INRIA", "Nadav Cohen": "Institute for Advanced Study", "Allan Jabri": "UC Berkeley", "Sa\u00fal A. Blanco": "Indiana University", "University of California Francisco Javier Sanchez-Lopez": "University of California, Irvine", "Yisen Wang": "Tsinghua University", "Charles Kuang": "The University of Wisconsin, Madison", "Andrew Wilson": "Cornell University", "Curtis \"Fjord\" Hawthorne": "Google Brain", "Olivier Buffet": "INRIA", "Csaba Szepesvari": "Deepmind", "Pierre-Luc Bacon": "McGill", "David Grangier": "Facebook", "Zhangyang Wang": "Texas A&M University", "Yaniv Taigman": "Facebook", "Amirali Aghazadeh": "Stanford University", "Jean Feng": "University of Washington", "Xingyuan Pan": "University of Utah", "Niki Kilbertus": "MPI T\u00fcbingen & Cambridge", "Samuli Laine": "NVIDIA Research", "Alexander Olshevsky": "", "Krishna Gummadi": "MPI-SWS", "Jakob Verbeek": "INRIA", "Roy Fox": "UC Berkeley", "Robin Ru": "University of Oxford", "Rachid Guerraoui": "EPFL", "Tom Walters": "DeepMind", "Mark Mcleod": "University of Oxford", "Yang Zhang": "Rice University", "Dino Oglic": "University of Bonn", "Yuan Zhou": "Indiana University Bloomington", "Ari S Morcos": "DeepMind", "Ashkan Norouzi-Fard": "EPFL", "Martin Jankowiak": "Uber AI Labs", "Telecom-ParisTech Chlo\u00e9 Clavel": "Telecom-ParisTech, Paris, France", "Manu Kaul": "IIT Hyderabad", "Shibani Santurkar": "MIT", "Devon Graham": "University of British Columbia", "James Cheng": "CUHK", "Nan Jiang": "Microsoft Research", "Daniel Ma": "The University of Melbourne", "Angelos Katharopoulos": "Idiap", "Wolfram Wiesemann": "Imperial College", "Demis Hassabis": "Deepmind", "Jan Kleindienst": "IBM Watson", "Adrien Taylor": "INRIA/ENS", "Qingyao Wu": "South China University of Technology", "Amjad Almahairi": "MILA, University of Montreal", "Tameem Adel": "University of Cambridge", "Hae Beom Lee": "UNIST", "Dominik Janzing": "Amazon Research T\u00fcbingen", "Jamie Smith": "Google", "Romain Couillet": "CentralSup\u00e9lec", "Georg Ostrovski": "DeepMind", "Damiano Binaghi": "Politecnico di Milano", "Arnab Bhattacharyya": "Indian Institute of Science", "Vishnu Natchu": "", "Yian Ma": "UC Berkeley", "Tatsunori Taniai": "RIKEN AIP", "Hongteng Xu": "InfiniaML, Inc.", "Stefan Falkner": "University of Freiburg", "Alexandra Brintrup": "", "Abigail Katoff": "MIT", "Simon Olofsson": "Imperial College London", "Grant Ayers": "Stanford", "Chelsea Finn": "UC Berkeley", "Lukas Ruff": "Hasso Plattner Institute", "Hidetoshi Shimodaira": "Kyoto University / RIKEN AIP", "Renjie Liao": "University of Toronto", "Keyulu Xu": "MIT", "Antonio Criminisi": "Microsoft", "Sham Kakade": "University of Washington", "Adria Gascon": "The Alan Turing Institute / Warwick University", "Jeff Clune": "Uber AI Labs", "Celestine D\u00fcnner": "IBM Research", "Piyush Grover": "Mitsubishi Electric Research Labs", "Alex Graves": "DeepMind", "Jie Shen": "Rutgers University", "Bin Dai": "Tsinghua University", "Sikun Yang": "TU Darmstadt", "Akash Srivastava": "University of Edinburgh", "Levent Sagun": "ENS/CEA", "Matej Balog": "University of Cambridge and MPI T\u00fcbingen", "Sanjay Shakkottai": "University of Texas at Austin", "Katya Scheinberg": "Lehigh University", "Praneeth Narayanamurthy": "Iowa State University", "Zhan Shi": "University of Illinois at Chicago", "Giulia DeSalvo": "Google Research", "Emmanuel Abbe": "", "Peyman Mohajerin Esfahani": "Delft University of Technology", "Sina Lin": "Microsoft", "Agniva Chowdhury": "Purdue University", "Dimitris Kalimeris": "Harvard University", "Devin Willmott": "University of Kentucky", "kyowoon Lee": "UNIST", "Caroline Uhler": "Massachusetts Institute of Technology", "Tsendsuren Munkhdalai": "Microsoft Research", "Deva Ramanan": "Carnegie Mellon University", "Sebastian Nowozin": "Microsoft Research", "Sinong Geng": "UW-Madison", "Muhammad Osama": "Uppsala University", "Yuanxiang Gao": "University of Toronto", "Ce Zhang": "ETH Zurich", "Ondrej Bajgar": "IBM Watson", "Armando Solar-Lezama": "MIT", "EECS Kurt Keutzer": "EECS, UC Berkeley", "Dennis Prangle": "Newcastle University", "Ilja Kuzborskij": "University of Milan", "Jiacheng Yang": "Shanghai Jiao Tong University", "Michael Auli": "Facebook", "Jakub Tomczak": "University of Amsterdam", "Difan Zou": "University of Virginia", "Karthik Subbian": "Facebook", "Pengtao Xie": "Carnegie Mellon University", "Kate Saenko": "Boston University", "Flavio Chierichetti": "Sapienza University", "Facebook Rob Fergus": "Facebook AI Research, NYU", "Gerard Arous": "", "Koulik Khamaru": "University Of California Berkeley", "George Konidaris": "Brown", "Vincent Zhuang": "Caltech", "Dane Corneil": "EPFL", "Marco Fraccaro": "Technical University of Denmark", "Mehran Mesbahi": "", "AmirEmad Ghassami": "UIUC", "Sergey Levine": "Berkeley", "Ohad Shamir": "Weizmann Institute of Science", "Robert Krauthgamer": "Weizmann Institute of Science", "Toryn Q Klassen": "University of Toronto", "Zengfeng Huang": "Fudan University", "Mingyan Liu": "University of Michigan, Ann Arbor", "Charu Sharma": "Indian Institute of Technology Hyderabad", "Andreas Doerr": "Bosch Center for Artificial Intelligence, Max Planck Institute for Intelligent Systems", "Ming Yan": "Michigan State University", "Raquel Urtasun": "University of Toronto", "Laurent Lessard": "University of Wisconsin-Madison", "Nina Balcan": "Carnegie Mellon University", "Mark Girolami": "Imperial College London", "Furong Huang": "University of Maryland College Park", "Siwei Wang": "Tsinghua University", "Xin Liu": "University of California, Davis", "Michael L. Littman": "Brown University", "Bobby Kleinberg": "Cornell", "Nati Srebro": "Toyota Technological Institute at Chicago", "Yichen Chen": "Princeton University", "James Zou": "Stanford University", "Jichuan Chang": "Google", "Yung-Kyun Noh": "Seoul National University", "Frederic Sala": "Stanford", "David Inouye": "Carnegie Mellon University", "Vijay Badrinarayanan": "Magic Leap Inc.", "Cristian R. Rojas": "KTH Royal Institute of Technology", "Amir Globerson": "Tel Aviv University, Google", "EPFL Pascal Fua": "EPFL, Switzerland", "Hui Li": "Ant Financial Services Group", "rong jin": "alibaba group", "Richard Valenzano": "Element AI", "Ruoxi Sun": "Columbia University", "Prathamesh Patil": "University of Pennsylvania", "Fernanda Vi\u00e9gas": "Google", "Josh V Dillon": "Google", "David Krueger": "Universit? de Montr?al", "Stephen Wright": "University of Wisconsin-Madison", "David Held": "Carnegie Mellon University", "David Wagner": "UC Berkeley", "Jihun Hamm": "The Ohio State University", "Umut Simsekli": "Telecom ParisTech", "Martin Wainwright": "University of California at Berkeley", "Gabriel Bender": "Google", "Lily Weng": "MIT", "Ursula Hebert-Johnson": "Stanford University", "Franz Franchetti": "Carnegie Mellon University", "Sue Zheng": "MIT", "Risi Kondor": "U. Chicago", "Liang Tong": "Vanderbilt University", "Jun Zhu": "Tsinghua University", "Pulkit Agrawal": "UC Berkeley", "Taesung Park": "UC Berkeley", "Fangwei Zhong": "Peking University", "Jaan Altosaar": "Princeton University", "Andre Barreto": "DeepMind", "Judy Hoffman": "UC Berkeley", "Sudanthi Wijewickrema": "University of Melbourne", "Yan Li": "Georgia Institute of Technology", "Huan Zhang": "UC Davis", "Alex d'Aspremont": "CNRS, Ecole Normale Superieure", "Wengong Jin": "MIT Computer Science and Artificial Intelligence Laboratory", "Aravindan Vijayaraghavan": "", "Benjamin Eysenbach": "Google", "Yoon Kim": "Harvard University", "Matthias Poloczek": "University of Arizona", "Department of Statistics Liam Paninski": "Department of Statistics, Columbia University", "Mohammad Ghavamzadeh": "Google DeepMind and INRIA", "Lijun Zhang": "Nanjing University", "Mingjun Zhong": "University of Lincoln", "El Mahdi El Mhamdi": "EPFL", "Jiri Hron": "University of Cambridge", "Xu Tan": "Microsoft Research", "Jianchao Yang": "Bytedance Inc.", "Christian Tjandraatmadja": "Carnegie Mellon University", "Yasaman Bahri": "Google Brain", "Ping Li": "Rugters University", "Emti Khan": "RIKEN", "Vincent Moens": "Universit\u00e9 catholique de Louvain", "Kevin Leyton-Brown": "University of British Columbia", "Ruben Villegas": "University of Michigan", "David Meger": "McGill University", "Andrew Lan": "Princeton University", "Hal Daume": "Microsoft Research", "Haihao Lu": "MIT", "Giambattista Parascandolo": "Max Planck Institute for Intelligent Systems and ETH Zurich", "Frank Wood": "University of Oxford", "Claudia Clopath": "Imperial College London", "Kamil Ciosek": "Oxford", "Rachit Dubey": "University of California, Berkeley", "Olga Diamanti": "Autodesk", "S\u00e9bastien Rouault": "EPFL", "Pavle Djordjevic": "ETH", "Ning Xu": "Snap", "Fabio Viola": "DeepMind", "Zheng Ke": "University of Chicago", "Zhenyu Liao": "L2S, CentraleSupelec", "Si Liu": "Oregon State University", "Thomas Moreau": "CMLA, ENS Paris-Saclay", "Ramina Ghods": "Cornell University", "Stephen Chestnut": "ETH Zurich", "Takuro Fukunaga": "RIKEN AIP", "Amir Khoshaman": "D-Wave systems Inc", "Xuan Zeng": "Fudan University", "Hossein Azizpour": "KTH", "Kean Ming Tan": "University of Minnesota Twin Cities", "Weidong Huang": "Tencent", "Yexiang Xue": "Purdue University", "huangxin Huang": "Ant Financial", "Misha Chertkov": "Los Alamos National Laboratory", "Raef Bassily": "", "Manik Dhar": "Stanford University", "Markus Wulfmeier": "University of Oxford", "Mung Chiang": "Purdue University", "Chris J Oates": "Newcastle University", "Benjamin Goldstein": "", "Yichen Zhu": "Peking University", "Diego Granziol": "Oxford", "Shakir Mohamed": "DeepMind", "Yonglong Tian": "MIT", "Bin Dong": "Peking University", "Christian Str\u00e4ssle": "University Hospital Zurich", "Steve Mussmann": "Stanford University", "Niki Parmar": "Google", "Ga\u00ebl RICHARD": "T\u00e9l\u00e9com ParisTech", "Ariel Jaffe": "Weizmann Institute of Science", "Yaroslav Ganin": "Montreal Institute for Learning Algorithms", "Jiaming Xu": "Duke University", "Jonathan Scarlett": "National University of Singapore", "Philip Yu": "UIC", "Dan Hendrycks": "UC Berkeley", "Yoonho Lee": "Pohang University of Science and Techonology", "Dylan Hadfield-Menell": "UC Berkeley", "Matthew Fellows": "University of Oxford", "Abhinav Verma": "Rice University", "Paavo Parmas": "Okinawa Institute of Science and Technology Graduate University", "Ian Walker": "Imperial College London", "Somayeh Sojoudi": "University of California, Berkeley", "Mingyi Hong": "University of Minnesota", "Amit Jayant Deshpande": "Microsoft Research", "Pavel Dvurechenskii": "Weierstrass Institute for Applied Analysis and Stochastics", "Aoxiao Zhong": "Zhejiang University", "Sherjil Ozair": "University of Montreal", "Aslan Tchamkerten": "Telecom ParisTech", "Dan Roy": "Univ of Toronto | Toronto", "Angela Zhou": "Cornell University", "Hamed Hassani": "University of Pennsylvania", "Thomas Dietterich": "(organization)", "Lin Wang": "", "Amir Dezfouli": "UNSW", "Scott Alfeld": "Amherst College", "loic landrieu": "IGN", "Mikolaj Binkowski": "Imperial College London", "Giacomo Boracchi": "Politecnico di Milano", "Alexey Kroshnin": "Institute for Information Transmission Problems", "Ahmed Douik": "California Institute of technology", "Valentin Khrulkov": "Skolkovo Institute Of Science And Technology", "Raghu Bollapragada": "Northwestern University", "Denis Yarats": "Facebook AI Research", "Daniel Sheldon": "University of Massachusetts Amherst", "Duane Boning": "MIT", "Jack Rae": "DeepMind", "Sanjiv Kumar": "Google Research, NY", "Julian Katz-Samuels": "University of Michigan", "Karl Tuyls": "DeepMind", "Regina Barzilay": "MIT CSAIL", "Marek Petrik": "University of New Hamoshire", "Jianfei Chen": "Tsinghua University", "Yitong Wang": "Tencent AI Lab", "Changyou Chen": "SUNY at Buffalo", "Jim Rehg": "Georgia Tech", "JD Co-Reyes": "UC Berkeley", "Paidamoyo Chapfuwa": "Duke University", "Yan Sun": "Purdue University", "Victoria Crawford": "University of Florida", "Jake Zhao": "NYU / Facebook AI Research", "Robin Vogel": "T\u00e9l\u00e9com ParisTech", "Chin-Wei Huang": "MILA", "Mengyuan Yan": "Stanford University", "Duhyeon Bang": "Yonsei univ.", "Kaushik Sinha": "Wichita State University", "Myle Ott": "Facebook", "Gunhee Kim": "Seoul National University", "Daniel Holtmann-Rice": "Google Inc", "Romain Cosentino": "Rice University", "Tianbing Xu": "Baidu Research, USA", "Daniel J. Mankowitz": "Technion", "Arthur Guez": "Google DeepMind", "Chunhua Shen": "University of Adelaide", "Yizhou Wang": "Peking University", "Zhenwen Dai": "Amazon.com", "Emmanuel M\u00fcller": "Hasso Plattner Institute", "Maarten de Rijke": "University of Amsterdam", "Helen King": "DeepMind", "Percy Liang": "Stanford University", "Zhengyuan Zhou": "Stanford University", "Tommi Jaakkola": "MIT", "Ron Meir": "Technion Israeli Institute of Technology", "Ciara Pike-Burke": "Lancaster University", "Kamyar Azizzadenesheli": "UC Irvine/ Stanford", "Gu-Yeon Wei": "", "Junxing Shi": "Purdue University", "Ness Shroff": "The Ohio State University", "Sreejith Kallummil": "Qualcomm India Private Limited", "Yarin Gal": "University of OXford", "Stuart Russell": "UC Berkeley", "University of California David Kirkby": "University of California, Irvine", "Pascale Kuntz": "LS2N", "Aonan Zhang": "Columbia University", "Gell\u00e9rt Weisz": "DeepMind", "Matilde Gargiani": "University of Freiburg", "Issei Sato": "University of Tokyo / RIKEN", "Uyeong Jang": "University of Wisconsin - Madison", "Edward Chien": "Massachusetts Institute of Technology", "Niao He": "UIUC", "Mohammad Reza Hesamzadeh": "KTH Royal Institute of Technology", "Andrew Tomkins": "Google", "Suraj Srinivas": "Idiap", "Thomas Unterthiner": "Johannes Kepler University Linz", "Christopher Holmes": "University of Oxford", "Dhruv Batra": "Georgia Institute of Technology / Facebook AI Research", "Giacomo Indiveri": "University of Zurich", "Zuofeng Shang": "Indiana University\u2013Purdue University Indianapolis", "M. Li": "University College London", "Aravind Srinivas": "UC Berkeley", "Ioannis Koutis": "", "Mete Ozay": "Tohoku University", "Stephen Tu": "UC Berkeley", "Yingyan Lin": "", "Xianzhong Ma": "Peking University", "James von Brecht": "CSULB", "John Paisley": "Columbia University", "Marius Miron": "Joint Research Centre of the European Commission", "Robert Freund": "MIT", "Kambis Veschgini": "University of Heidelberg", "Mike Wei": "University at Buffalo", "Keegan Kang": "Singapore University Of Technology And Design", "Hanna Sumita": "National Institute of Informatics", "Elias Bareinboim": "Purdue", "Andre Filipe Torres Martins": "Instituto de Telecomunicacoes", "Christoph Lampert": "IST Austria", "Amin Karbasi": "Yale", "koray kavukcuoglu": "DeepMind", "Jianmin Wang": "Tsinghua University", "Thore Graepel": "DeepMind", "Bowei Yan": "University of Texas at Austin", "William Macready": "D-Wave", "Sebastien Bubeck": "Microsoft Research", "Gang Niu": "RIKEN", "Nicholas Sidiropoulos": "University of Virginia", "Marc'Aurelio Ranzato": "Facebook AI Research", "Roberta Raileanu": "NYU", "University of California Moritz Hardt": "University of California, Berkeley", "Travis Gibson": "Harvard Medical School", "Siyuan Ma": "The Ohio State University", "Tomer Michaeli": "Technion", "Amir Zandieh": "EPFL", "Anish Athalye": "MIT CSAIL", "Shengyang Sun": "University of Toronto", "David Abel": "Brown University", "Yi Xu": "The University of Iowa", "Ziteng Sun": "Cornell University", "Dennis Wei": "IBM Research", "Ehsan Kazemi": "Yale", "Vignesh Ganapathiraman": "University of Illinois at Chicago", "Fabio Pardo": "Imperial College London", "Xian Wu": "Stanford University", "Andrew Dai": "Google Brain", "Martin Jaggi": "EPFL", "Matthew Smith": "McGill University", "Mehrdad Farajtabar": "Georgia Tech", "Aaditya Ramdas": "UC Berkeley", "Petar Kormushev": "Imperial College London", "Neil Lawrence": "Amazon", "Barret Zoph": "Google", "chao qu": "technion", "Richard Liaw": "UC Berkeley", "Raman Arora": "Johns Hopkins University", "Christos Kaplanis": "Imperial College London", "Shuo Zhou": "The University of Melbourne", "Nicolas Flammarion": "UC Berkeley", "Kaiwen Zhou": "The Chinese University of Hong Kong", "Mohamed Zaki": "University of Cambridge", "Yuancheng Zhu": "University of Pennsylvania", "Bo Wang": "Hikvision Research Institue", "Claudio Michaelis": "Universty of T\u00fcbingen", "Ian Goodfellow": "Google Brain", "Stephen Roberts": "University of Oxford", "Thang Luong": "Google Brain", "Huidong Liu": "Stony Brook University", "Herke van Hoof": "McGill University", "Swarat Chaudhuri": "Rice University", "Tomer Koren": "Google Brain", "Randall Balestriero": "Rice University", "Jiefeng Chen": "University of Wisconsin-Madison", "Yizhe Zhang": "Duke University", "John Lafferty": "Yale University", "Herman Kamper": "Stellenbosch University", "Mohammad Mehrabi": "Sharif University of Technology", "Thiago Serra": "Carnegie Mellon University", "Jian Zhang": "Apple Inc.", "Mikhail Belkin": "Ohio State University", "Lek-Heng Lim": "University of Chicago", "Sepp Hochreiter": "Johannes Kepler University Linz", "Zornitsa Kozareva": "", "Zhiting Chen": "Cornell University", "Suprovat Ghoshal": "Indian Institute of Science", "Yaqing WANG": "HKUST", "Ying Wu": "Northwestern University", "Jiaxiang Wu": "Tencent AI Lab", "Andrew Cotter": "Google", "Sixie Yu": "Vanderbilt University", "Geoff Gordon": "Carnegie Mellon University", "Georg Gerber": "Harvard Medical School", "Chris Cremer": "University of Toronto", "Yew Soon ONG": "Nanyang Technological University", "Xingdi Yuan": "Microsoft Maluuba", "Wulfram Gerstner": "EPFL", "Sheila McIlraith": "University of Toronto", "Mihaela Rosca": "DeepMind", "Thomas Lampe": "DeepMind", "Zhitang Chen": "Huawei Noah\u2019s Ark Lab", "Qiang Qiu": "Duke University", "Vineet Gupta": "Google", "Ken Goldberg": "UC Berkeley", "Danilo J. Rezende": "DeepMind", "Tao Yao": "penn state university", "Wojciech Czarnecki": "DeepMind", "Eugenio Culurciello": "Nil", "Volodymyr Kuleshov": "Stanford University", "Stefan Szeider": "TU Wien", "Jane Wang": "DeepMind", "Shie Mannor": "Technion", "Miles Lopes": "University of California, Davis", "Aaron Courville": "University of Montreal", "Eliya Nachmani": "Facebook AI Research and Tel Aviv University", "Mao Ye": "PURDUE UNIVERSITY", "Graham Cormode": "University of Warwick", "Seungil You": "Google", "Louis Filstroff": "CNRS, Toulouse", "Dan Belov": "Google", "Marko Mitrovic": "Yale University", "Tuomas Haarnoja": "UC Berkeley", "David Blei": "Columbia University", "Zeyuan Allen-Zhu": "Microsoft Research AI", "Wenlong Mou": "UC Berkeley", "Sven Schmit": "Stanford University", "Sabyasachi Chatterjee": "Sabyasachi Chatterjee", "Christian Daniel": "TU Darmstadt", "Huanyu Zhang": "Cornell University", "Shaoan Xie": "Sun Yat-sen University", "Ronan Fruit": "Inria Lille Nord-Europe", "Tianyu Pang": "Tsinghua University", "Doina Precup": "McGill University / DeepMind", "Miika Aittala": "MIT", "Hongge Chen": "MIT", "LIWEI WU": "University of California, Davis", "Aaron Klein": "University of Freiburg", "Jackson Gorham": "STANFORD", "Jason Pacheco": "Brown University", "Fred Hamprecht": "Heidelberg Collaboratory for Image Processing", "Jingwei Liang": "University of Cambridge", "Namrata Vaswani": "Iowa State University, USA", "Tom Schaul": "DeepMind", "Scott Yang": "D. E. Shaw & Co.", "Gintare Karolina Dziugaite": "University of Cambridge", "Ronald Ortner": "Montanuniversitaet Leoben", "Liang Chen": "Sun Yat-sen University", "Ben Glocker": "Imperial College London", "Will Hamilton": "Stanford University", "Mike Lewis": "Facebook", "Ioannis Antonoglou": "Deepmind", "Lu Jiang": "Google", "Christopher Pal": "\u00c9cole Polytechnique de Montr\u00e9al", "Nikolay Jetchev": "Zalando Research", "Shuaiwen Wang": "Columbia University", "Zachary Lipton": "Carnegie Mellon University", "Ola Svensson": "EPFL", "Tommaso Furlanello": "University of Southern California", "Masanori SUGANUMA": "RIKEN AIP / Tohoku University", "Zhitao Ying": "Stanford University", "Raghu Meka": "UCLA", "Wenda Zhou": "Columbia University", "Wei Chen": "Microsoft Research", "Robert Nishihara": "Unknown", "Karen Simonyan": "DeepMind", "Suriya Gunasekar": "Toyota Technological Institute at Chicago", "Jiaming Song": "Stanford", "Xiuyuan Cheng": "Duke University", "Jilles Dibangoye": "INRIA", "Andrew Ilyas": "Massachusetts Institute of Technology", "Kuan Han": "Purdue University", "Tze Meng Low": "Carnegie Mellon University", "Jinwoo Shin": "KAIST", "Will Dabney": "DeepMind", "Matthias Hein": "University of Tuebingen", "Volkan Cevher": "EPFL", "Vitaly Levdik": "Imperial College London", "Xiao Zhang": "University of Virginia", "Nick J Foti": "University of Washington", "Max Welling": "University of Amsterdam", "Clay Scott": "University of Michigan", "Bo Dai": "Georgia Institute of Technology", "Kaiqing Zhang": "University of Illinois at Urbana-Champaign (UIUC)", "Armand Joulin": "Facebook", "Calvin Seward": "Zalando Research", "Haipeng Luo": "University of Southern California", "Siavash Haghiri": "University of T\u00fcbingen", "Dilin Wang": "UT Austin", "Max Jaderberg": "DeepMind", "Yan Liu": "University of Southern California", "Yoshua Bengio": "U. Montreal", "Yura Burda": "OpenAI", "Satyen Kale": "Google Research", "Albert Gu": "Stanford University", "Alvaro Sanchez": "DeepMind", "Somesh Jha": "University of Wisconsin, Madison", "Chunyuan Li": "Duke University", "ChangYong Oh": "University of Amsterdam", "Emily Fox": "University of Washington", "Harri L\u00e4hdesm\u00e4ki": "Aalto University", "Artur Dubrawski": "CMU", "Dave Helmbold": "", "Thanh Nguyen": "Iowa State University", "Eran Yahav": "Technion", "Kevin Murphy": "Google", "Joseph Gonzalez": "UC Berkeley", "Mathurin MASSIAS": "INRIA", "Elliot Creager": "University of Toronto", "Yuu Jinnai": "Brown University", "Weili Nie": "Rice University", "Hideaki Imamura": "The University of Tokyo", "Yann Ollivier": "Facebook Artificial Intelligence Research", "Brenden Lake": "New York University", "Paolo Frasconi": "University of Florence", "Evgeny Andriyash": "D-Wave", "Lin Ma": "Tencent AI Lab", "Yisong Yue": "Caltech", "Matt Bonakdarpour": "University of Chicago", "Jaime Fisac": "UC Berkeley", "Nina Mishra": "Amazon", "Laurent Charlin": "McGill University", "Sivaraman Balakrishnan": "Carnegie Mellon University", "Edoardo Remelli": "epfl", "Anima Anandkumar": "Amazon", "Jelena Diakonikolas": "Boston University", "Diana Borsa": "DeepMind", "stephen boyd": "stanford university", "Emma Brunskill": "Stanford University", "Amir-massoud Farahmand": "Vector Institute", "Chuan Chen": "Sun Yat-sen University", "Yevgeniy Vorobeychik": "Vanderbilt University", "Morteza Zadimoghaddam": "Google", "Xiang Ren": "University of Southern California", "Erik Talvitie": "Franklin & Marshall College", "Karren Yang": "Massachusetts Institute of Technology", "Nicolas Heess": "Google DeepMind", "Alex Alemi": "Google", "M van der Schaar": "UCLA", "Olivier Sigaud": "Sorbonne University", "Guy Blanc": "Stanford University", "Wenlong Lyu": "Fudan University", "Manolis Tsakiris": "Johns Hopkins University", "Subham S Sahoo": "Indian Institute of Technology", "Thomas Leung": "Google Inc", "Catherine Olsson": "Google Brain", "Javier Gonz\u00e1lez": "Amazon", "Xueying Guo": "University of California Davis", "Siddhant Jayakumar": "DeepMind", "Nevena Lazic": "Google", "Mohamed Ishmael Belghazi": "MILA", "Igor Babuschkin": "DeepMind", "Kamalika Chaudhuri": "University of California at San Diego", "Christoph Dann": "Carnegie Mellon University", "MIT Ronitt Rubinfeld": "MIT, TAU", "Alberto Lumbreras": "CNRS - IRIT", "Chiara Cammarota": "King's College London", "Xinwei Sun": "Peking University", "Qiang Sun": "University of Toronto", "Zita Marinho": "Carnegie Mellon University", "Timothee Lacroix": "Facebook", "Murray Shanahan": "Imperial College London", "Aditya Nori": "Microsoft Research Cambridge", "Alexander Smola": "Amazon", "Alessio Micheli": "Universita di Pisa", "Jon Hasselgren": "NVIDIA", "Dylan Foster": "Cornell University", "Slim Essid": "Telecom ParisTech", "Yuan Jiang": "Nanjing University", "Dong Yin": "UC Berkeley", "Lisa Zhang": "University of Toronto", "Benjamin Paa\u00dfen": "Bielefeld University", "Oleg Arenz": "TU Darmstadt", "Chaoqi Wang": "University of Toronto", "Rif Saurous": "", "Chang Liu": "Tsinghua University", "Bingyi Kang": "National University of Singapore", "Risto Miikkulainen": "UT Austin - Sentient Technologies", "Peilin Zhong": "Columbia University", "Hongbao Zhang": "Petuum Inc", "Sat Chatterjee": "Two Sigma Investments", "Matth\u00e4us Kleindessner": "Rutgers University", "Yuling Yao": "Columbia University", "Pierre Vandergheynst": "\u00c9cole polytechnique f\u00e9d\u00e9rale de Lausanne", "Manzil Zaheer": "Carnegie Mellon University", "Yiping Lu": "Peking University", "Claire Cardie": "Cornell University", "Chiyuan Zhang": "Google", "Chen-Yu Lee": "", "Wenruo Bai": "University of Washington", "Leonard Hasenclever": "DeepMind", "Zico Kolter": "Carnegie Mellon University", "Shiva Kasiviswanathan": "Amazon", "Lucas Deecke": "University of Edinburgh", "Yi Li": "Nanyang Technological University", "Ryan Rogers": "Apple", "Shinji Ito": "NEC Corporation", "Rina Barber": "", "Sebastian Ordyniak": "University of Sheffield", "Tom Van de Wiele": "DeepMind", "Tejas Kulkarni": "DeepMind", "Ayush Jain": "UC San Diego", "Mengdi Wang": "Princeton University", "Lasse Espeholt": "DeepMind", "Song-Chun Zhu": "UCLA", "Vijayaraghavan Murali": "Rice University", "Yuejie Chi": "CMU", "Yoav Goldberg": "Bar Ilan University", "Xiaojie Jin": "National University of Singapore", "Gary Becigneul": "ETHZ", "Tamas Keviczky": "Delft University of Technology", "Rodrigo Barros": "PUCRS", "Mohammad Mahdi Khalili": "University of Michigan", "Daisy Stanton": "", "Vaggos Chatziafratis": "Stanford University", "Hossein Esfandiari": "Harvard University", "Mario Geiger": "EPFL", "kirthevasan kandasamy": "CMU", "Justin Gilmer": "Google Brain", "Michael A Osborne": "U Oxford", "Fabian Pedregosa": "UC Berkeley", "Akihiro Yabe": "NEC Corporation", "Francisco Ruiz": "Columbia University", "Jorge Nocedal": "Northwestern University", "Corinna Cortes": "Google Research", "Jiaxuan You": "Stanford University", "Emilio Parisotto": "Carnegie Mellon University", "Daizong Ding": "Fudan University", "Rie Johnson": "RJ Research Consulting", "Jan Peters": "TU Darmstadt + Max Planck Institute for Intelligent Systems", "Arthur Mensch": "Inria Parietal", "Han-Jia Ye": "Nanjing University", "Jinsung Yoon": "University of California, Los Angeles", "Yingzhen Li": "University of Cambridge", "Norman Casagrande": "DeepMind", "Siddhartha Srinivasa": "University of Washington", "Martin Takac": "Lehigh University", "Giulio Biroli": "", "Francois-Xavier Briol": "University of Warwick", "David Duvenaud": "University of Toronto", "Arash Mehrjou": "Max Planck Institute for Intelligent Systems", "Yong Guo": "South China University of Technology", "Weizhong Zhang": "Tencent AI Lab", "Thomas Hofmann": "ETH Zurich", "Alexander Rush": "Harvard University", "Vlad Firoiu": "", "Yury Ustinovskiy": "Princeton University", "He Zhao": "FIT, Monash University", "Keith Levin": "University of Michigan", "Junjie Ma": "Columbia University", "Daan Wierstra": "Google DeepMind", "Itzhak Tamo": "Tel-Aviv University", "Pieter Abbeel": "OpenAI / UC Berkeley", "Mingrui Liu": "The University of Iowa", "Alessandro Lazaric": "Facebook AI Research", "Wray Buntine": "Monash University", "Olgica Milenkovic": "University of Illinois UC", "Zhengbing Bian": "Quadrant.ai, D-Wave Systems Inc.", "Jon Kleinberg": "Cornell University", "JP Vert": "ENS Paris", "Chris Dyer": "DeepMind", "Kyriacos Shiarlis": "University of Amsterdam", "Xuhong LI": "CNRS/UTC Heudiasyc", "Albert Shaw": "Georgia Tech", "Leonidas Guibas": "Stanford University", "Milad Hashemi": "Google", "Cijo Jose": "Idiap Research Institute", "Jelena Luketina": "The University of Oxford", "Maximilian Ilse": "University of Amsterdam", "Zhifeng Gao": "Tsinghua University", "Wenlin Wang": "Duke University", "Yancheng Yuan": "National University of Singapore", "Rizal Fathony": "University of Illinois at Chicago", "Yitao Liang": "UCLA", "Cedric Fevotte": "CNRS", "Toniann Pitassi": "University of Toronto", "Sungsoo Ahn": "KAIST", "Quanquan Gu": "University of Virginia--> UCLA", "Diego Klabjan": "Northwestern University", "Barnab\u00e1s P\u00f3czos": "CMU", "Qingyun Sun": "Stanford University", "Lechao Xiao": "Google Brain", "Soumik Mandal": "", "Robert Busa-Fekete": "Yahoo Research", "Tom B Brown": "Google Brain", "Junya Honda": "University of Tokyo / RIKEN", "Adji Bousso Dieng": "Columbia University", "Smita Krishnaswamy": "Yale University", "Stephan Mandt": "Disney Research", "Shipra Agarwal": "Columbia", "Joel Burdick": "Caltech", "Dimitris Papailiopoulos": "ECE at University of Wisconsin-Madison", "David Wipf": "Microsoft Research", "Jackson Wang": "Univeristy of Toronto", "Arno Solin": "Aalto University", "Qiang Ye": "University of Kentucky", "Aditya Bhaskara": "University of Utah", "Nenghai Yu": "USTC", "Marcus Gallagher": "University of Queensland", "Pierre-Yves Oudeyer": "Inria", "Dominik Grewe": "", "Andrew Miller": "Harvard", "Ganggang Xu": "SUNY-Binghamton University", "Meisam Razaviyayn": "University of southern California", "Tom Goldstein": "University of Maryland", "Sheetal Kalyani": "IIT Madras", "Rong Ge": "Duke University", "Venkatesh Saligrama": "Boston University", "Rotem Mulayoff": "Technion", "Junier Oliva": "Carnegie Mellon University", "Jun Gao": "Peking University", "Richard E Turner": "University of Cambridge", "Ji Liu": "University of Rochester", "Piotr Bojanowski": "Facebook", "Yanan Sui": "Caltech / Stanford", "Hado van Hasselt": "DeepMind", "Partha Ranganathan": "Google, USA", "Kevin Swersky": "Google Brain", "Jiashang Liu": "The Ohio State University", "Han Bao": "The University of Tokyo", "Michael E. Houle": "National Institute of Informatics", "George van den Driessche": "DeepMind", "Franck Iutzeler": "Univ. Grenoble Alpes", "Tuan Anh Le": "University of Oxford", "Yasuhiro Fujita": "Preferred Networks, Inc.", "Seb Noury": "DeepMind", "Michael Tschannen": "ETH Zurich", "Jianbo Chen": "University of California, Berkeley", "Itay Safran": "Weizmann Institute of Science", "Jingwei Zhuo": "Tsinghua University", "Tao Qin": "Microsoft Research Asia", "Florian Wenzel": "University of Kaiserslautern", "Andrey Zhitnikov": "Technion", "Alexandre Lacoste": "Element AI", "Samet Oymak": "University of California, Riverside", "Cristiano Cervellera": "National Research Council", "Huasen Wu": "Twitter", "Philip Bachman": "Microsoft Research", "Maruan Al-Shedivat": "Carnegie Mellon University", "Riccardo Grazzi": "Istituto Italiano di Tecnologia", "Pavel Serdyukov": "Yandex", "Emmanuel Ekwedike": "Princeton University", "Tim Harley": "DeepMind", "Eric Balkanski": "Harvard", "Steve Renals": "University of Edinburgh", "Douwe Kiela": "Facebook AI Research", "Mahdi Milani Fard": "Google", "Martin Wattenberg": "Google", "Li Chen": "Department of Electrical and Computer Engineering, University of Toronto", "J\u00e9r\u00f4me Malick": "CNRS", "Christos Kozyrakis": "Stanford University", "Brian Ziebart": "University of Illinois at Chicago", "Taiji Suzuki": "The University of Tokyo / RIKEN", "Frederic Koriche": "CRIL UMR CNRS 8188, Univ. Artois", "Wei Shen": "Shanghai University", "Yuchen Zhou": "University of Wisconsin, Madison", "Boaz Nadler": "Weizmann Institute of Science", "Zaiyi Chen": "University of Science and Technology of China", "Dian Zhou": "Department of Electrical Engineering The University of Texas at Dallas Richardso", "Sebastian Claici": "MIT", "John Peebles": "MIT", "Mahsa Taziki": "EPFL", "Quanming Yao": "4Paradigm", "Jiaman Li": "University of Toronto", "Duy Nguyen-Tuong": "Bosch Center for AI", "Ali Taylan Cemgil": "Bogazici University", "Maurizio Filippone": "Eurecom", "Charles Qi": "Stanford University", "Alexander Ecker": "University of T\u00fcbingen", "Rajat Sen": "University of Texas at Austin", "Carl Muroi": "University Hospital Zurich", "Mehdi S. M. Sajjadi": "Max Planck Institute for Intelligent Systems", "Todd Millstein": "University of California, Los Angeles", "Ivan Oseledets": "Skoltech", "Florence d'Alche-Buc": "T\u00e9l\u00e9com ParisTech, Universit\u00e9 Paris-Saclay,Paris, France", "Gal Dalal": "", "Adam Santoro": "DeepMind", "Alexander Gasnikov": "Moscow Institute of Physics and Technology", "Or Sheffet": "University of Alberta", "Hang Wu": "Georgia Institute of Technology", "Alon Orlitsky": "UCSD", "Shutao Xia": "Tsinghua University", "Daniel Soudry": "Technion", "Cagatay Yildiz": "Aalto University", "Dilip S. Arumugam": "Brown University", "Shubhendu Trivedi": "Toyota Technological Institute", "Ian Yen": "Carnegie Mellon University", "Praneeth Karimireddy": "EPFL", "Salar Fattahi": "UC Berkeley", "Haiguang Wen": "Purdue University", "Yangchen Pan": "University of Alberta", "Ofir Nachum": "Google Brain", "Benjamin Recht": "Berkeley", "Stefan Depeweg": "TU Munich", "Rashish Tandon": "Apple", "Justin Solomon": "MIT", "Pan Li": "University of Illinois Urbana-Champaign", "Aarti Singh": "Carnegie Mellon University", "Saverio Salzo": "Istituto Italiano di Tecnologia", "Gail Weiss": "Technion", "Runchao Ma": "University of Iowa", "DePaul Iyad Kanj": "DePaul University, Chicago", "Andriy Mnih": "DeepMind", "Lior Wolf": "Facebook AI Research and Tel Aviv University", "Jiong Zhang": "University of Texas at Austin", "Ashish Vaswani": "Google Brain", "Yijie Guo": "University of Michigan", "David GT Barrett": "DeepMind", "Kai Zhong": "University of Texas at Austin", "Yinlam Chow": "DeepMind", "Ron Amit": "Technion \u2013 Israel Institute of Technology", "Christopher Metzler": "Rice University", "Hariank Muthakana": "Carnegie Mellon University", "Lorenz M\u00fcller": "ETH Zurich and University of Zurich", "Weinan Zhang": "Shanghai Jiao Tong University", "Pranjal Awasthi": "Rutgers University", "Richard Zhang": "University of California, Berkeley", "Leslie Kaelbling": "(organization)", "Thodoris Lykouris": "Cornell University", "Jacob Buckman": "Google", "Bamdev Mishra": "Microsoft", "Aviral Kumar": "IIT Bombay", "Marten van Dijk": "University of Connecticut", "Alberto Maria Metelli": "Politecnico di Milano", "Yi Wang": "Rolls-Royce Singapore", "Vladimir Braverman": "Johns Hopkins University", "Yibo Lin": "UT-Austin", "Ben Poole": "Stanford University", "Yale Song": "Microsoft AI & Research", "Colin Raffel": "Google", "Frank Perbet": "DeepMind", "Bin Gu": "University of Pittsburgh", "Zhen Liu": "Georgia Tech", "Russell Tsuchida": "The University of Queensland", "Rudolf Kadlec": "IBM Watson", "Augustus Odena": "Google Brain", "Daniel Rueckert": "Imperial College London", "JesseEngel Engel": "Google Brain", "Li-Jia Li": "Google", "David Sontag": "Massachusetts Institute of Technology", "Inst. of Technology Carlo Fischione": "Royal Inst. of Technology, KTH", "Alexander Binder": "Singapore University of Technology and Design", "Borja de Balle Pigem": "Amazon Research", "Baochun Li": "University of Toronto", "Daniel C. Castro": "Imperial College London", "Junzhou Huang": "University of Texas at Arlington / Tencent AI Lab", "Matt Amodio": "Yale University", "Lingjiao Chen": "University of Wisconsin-Madison", "Arash Tavakoli": "Imperial College London", "Wei Liu": "Tencent AI Lab", "Ben Krause": "University of Edinburgh", "Emmanuel Kahembwe": "Edinburgh University", "Julien Martel": "ETH Zurich", "Xiaoyu Wang": "-", "CITEC Barbara Hammer": "CITEC, Bielefeld University", "Guy Rothblum": "Weizmann Institute of Science", "Alex Matthews": "University of Cambridge", "Aaron Roth": "University of Pennsylvania", "Yixin Wang": "Columbia University", "Shimon Whiteson": "University of Oxford", "Guang Cheng": "Purdue University", "xue wang": "THE PENNSYLVANIA STATE UNIVERSITY", "Zhao Song": "UT-Austin", "Xianfeng GU": "Stony Brook University", "Stefano Ermon": "Stanford University", "Tian Tian": "Tsinghua University", "Mark Rowland": "University of Cambridge", "Michael Mitzenmacher": "Harvard University", "Marco Gaboardi": "Univeristy at Buffalo", "Ping Tak Tang": "Intel Corporation", "Matteo Pirotta": "SequeL - Inria Lille - Nord Europe", "Charles Blundell": "DeepMind", "Abhishek Gupta": "UC Berkeley", "Wei Zhang": "IBM Research", "Travis Dick": "CMU", "Ahmed M. Alaa Ibrahim": "UCLA", "Jayesh Gupta": "Stanford University", "Tim Lillicrap": "Google DeepMind", "Yonathan Efroni": "Technion", "J. Smith": "University of Florida", "Daisuke Hatano": "RIKEN AIP", "Sunita Sarawagi": "IIT Bombay", "Daniel Jiang": "University of Pittsburgh", "Samuel Ainsworth": "University of Washington", "Bernhard Sch\u00f6lkopf": "MPI for Intelligent Systems T\u00fcbingen, Germany", "Lirong Xia": "RPI", "Laurent Itti": "University of Southern California", "Rob Fergus": "Facebook / NYU", "Marco Molinaro": "PUC-RIO", "Yaodong Yang": "University College London", "Matthieu Wyart": "", "Jing Wang": "Cornell University", "Jeff Bilmes": "UW", "Ahmed Hefny": "Carnegie Mellon University", "Bryan Van Scoy": "University of Wisconsin--Madison", "Ravi Kumar": "Google", "Trevor Campbell": "MIT", "Kim-Chuan Toh": "National University of Singapre", "Rory sayres": "Google", "Jian Peng": "UIUC", "Gauthier Gidel": "MILA", "Thomas Gaertner": "The University of Nottingham", "Jeremy Bernstein": "Caltech", "Qihang Lin": "Univ Iowa", "Yunbo Wang": "Tsinghua University", "Jonathan Dodge": "Oregon State University", "Guillaume Pouliot": "University of Chicago", "Laurent Oudre": "Universite Paris 13", "Zoubin Ghahramani": "University of Cambridge & Uber", "James Wexler": "Google", "Daniel Zoran": "DeepMind", "Wen Sun": "Carnegie Mellon University", "Yee Teh": "DeepMind", "Mingda Qiao": "IIIS, Tsinghua University", "Rosemary Nan Ke": "MILA, Polytechnique Montreal", "Josh Merel": "DeepMind", "Ruth Misener": "Imperial College London", "Panos Achlioptas": "Stanford", "Pradeep Ravikumar": "Carnegie Mellon University", "James Jordon": "University of Oxford", "Michael Gutmann": "University of Edinburgh", "Gautam Kamath": "MIT", "Jun-Yan Zhu": "MIT", "Simon Du": "Carnegie Mellon University", "Brendan O'Donoghue": "DeepMind", "Kristian Hartikainen": "UC Berkeley", "Ian Fischer": "Google", "Saber Salehkaleybar": "Sharif University of Technology", "Qiang Liu": "UT Austin", "Shivani Agarwal": "University of Pennsylvania", "Aran Khanna": "Dolores Technologies", "Weiyang Liu": "Georgia Tech", "RJ Skerry-Ryan": "Google, Inc.", "Akshay Soni": "Yahoo Research", "Hongseok Namkoong": "Stanford University", "Bo Jiang": "USC", "Yaodong Yu": "University of Virginia", "Mathieu Blondel": "NTT", "Joelle Pineau": "McGill University / Facebook", "Zhenyu Wu": "Texas A&M University", "Jinghui Chen": "University of Virginia", "Yash Deshpande": "Massachusetts Institute of Technology", "Jordan Ash": "Princeton University", "Sarah Dean": "UC Berkeley", "Jakob Uszkoreit": "", "Richard Zemel": "Vector Institute", "Mattias Teye": "KTH / EA SEED", "Arash Vahdat": "Quadrant.ai, D-Wave", "Guodong Zhang": "University of Toronto", "PHUONG HA NGUYEN": "University of Connecticut", "Maximilian Igl": "University of Oxford", "MILA Zhouhan Lin": "MILA, University of Montreal", "Akshay Krishnamurthy": "UMass", "Carl E Rasmussen": "Cambridge University", "Yi Wu": "UC Berkeley", "Aditya Gilra": "University of Bonn", "Samuel Schoenholz": "Google Brain", "Gregory Farquhar": "University of Oxford", "Shuyang Dai": "Duke University", "Hanjun Dai": "Georgia Tech", "Hiroyuki Kasai": "The University of Electro-Communications", "Yuan Cao": "Princeton University", "Zhe Zeng": "Zhejiang University", "Siddharth Srivastava": "Arizona State University", "Cho-Jui Hsieh": "University of California, Davis", "Xi Chen": "covariant.ai", "Siyuan Qiao": "Johns Hopkins University", "Niladri S Chatterji": "UC Berkeley", "Yi Zhang": "Princeton University", "Vahab Mirrokni": "Google Research", "Pratik Kumar Jawanpuria": "Microsoft", "Minhao Cheng": "UC Davis", "Shai Carmi": "The Hebrew University of Jerusalem", "Chao Du": "Tsinghua University", "Raul Rabadan": "Columbia University Medical Center", "Wei Pin Wong": "Singapore University of Technology and Design", "Matteo Papini": "Politecnico di Milano", "Wu Lin": "University of British Columbia", "Hadi Daneshmand": "ETH Zurich", "Boba Mitrovic": "EPFL", "Robert Bamler": "Disney Research", "Fanhua Shang": "The Chinese University of Hong Kong", "Peilin Zhao": "Artificial Intelligence Department, Ant \u200bFinancial", "Bin Hu": "University of Wisconsin-Madison", "Stefanie Jegelka": "MIT", "Fan Yang": "Fudan University", "Adam Lerer": "Facebook AI Research", "Lionel NI": "University of Macau", "Sol-A Kim": "UNIST", "Sam Wiseman": "Harvard University", "Ying Sheng": "", "Rodrigo A Toro Icarte": "University of Toronto", "Quoc Le": "Google Brain", "Junwei Lu": "", "Philip Isola": "UC Berkeley", "Jianfeng Feng": "Fudan University", "Dan Rosenbaum": "DeepMind", "Jun Wang": "UCL", "Steve Huntsman": "BAE Systems FAST Labs", "Jacob Gardner": "Cornell University", "Alexei Efros": "UC Berkeley", "Jiyuan Zhang": "Cargenie Mellon University", "Dumitru Erhan": "Google Brain", "Stefan Lee": "Georgia Institute of Technology", "Marco Carone": "University of Washington", "Mahesh Mukkamala": "Saarland University", "Zhao Chen": "Magic Leap, Inc", "Martin Reqiang Min": "NEC Laboratories America", "Ion Stoica": "UC Berkeley", "Simon Osindero": "DeepMind", "Zhiwei Wu": "Microsoft Research", "Ilias Zadik": "MIT", "Ioannis Mitliagkas": "MILA, UdeM", "Danny Karmon": "Bar Ilan University", "Mohammad Norouzi": "Google Brain", "Wenhan Luo": "Tencent AI Lab", "Alan Yuille": "Johns Hopkins University", "Ehsan Asadi Kangarshahi": "University of Cambridge", "Tarun Kathuria": "UC Berkeley", "Tetsuya Hada": "Recruit Technologies Co. Ltd.", "Alexey Drutsa": "Yandex; MSU", "Maheshakya Wijewardena": "University of Utah", "Bob Adolf": "Harvard University", "Chenyang Tao": "Duke University", "R Srikant": "UIUC", "Jian Ma": "Carnegie Mellon University", "Guy Van den Broeck": "University of California, Los Angeles", "James Martens": "DeepMind", "Yeonwoo Jeong": "Seoul National University", "Jonatas Wehrmann": "Pontif\u00edcia Universidade Catolica do Rio Grande do Sul - PUCRS", "Max Simchowitz": "UC Berkeley", "Jost Springenberg": "DeepMind", "Xuechen Li": "University of Toronto", "Adrian Weller": "University of Cambridge, Alan Turing Institute", "Eyke H\u00fcllermeier": "Paderborn University", "Chengtao Li": "MIT", "Trefor Evans": "University of Toronto", "Anshumali Shrivastava": "Rice University", "Ashok Veeraraghavan": "Rice University", "Bin Hong": "Zhejiang University", "Ricardo Cerri": "UFSCAR", "Thomas LUCAS": "Inria", "Rui Luo": "UCL", "Ryohei Fujimaki": "-", "Tingran Gao": "University of Chicago", "Sebastien Racaniere": "DeepMind", "Defeng Sun": "The Hong Kong Polytechnic University", "Fei Ren": "Google", "Noah Simon": "University of Washington", "Pascal Vincent": "U Montreal", "Panayotis Mertikopoulos": "CNRS", "Omid Keivani": "Wichita State University", "Avinava Dubey": "Carnegie Mellon University", "Octavian-Eugen Ganea": "ETH Zurich", "Tong Zhang": "Tecent AI Lab", "Tom Griffiths": "UC Berkeley", "Gautam Dasarathy": "Rice University", "Yunlong Jiao": "University of Oxford", "Mateo Rojas-Carulla": "Cambridge/MPI", "Alp Yurtsever": "EPFL", "robert Calderbank": "Duke University", "Neil Rabinowitz": "DeepMind", "Adam Kosiorek": "University of Oxford", "Qian Yang": "University of Pittsburgh", "Alan Kuhnle": "University of Florida", "Zhengping Che": "University of Southern California", "Dave Zachariah": "Uppsala University", "Jiezhang Cao": "South China University of Technology", "Benjamin Van Roy": "Stanford University", "Yudong Chen": "Cornell University", "Hoang M Le": "Caltech", "Daniel Robinson": "Johns Hopkins University", "Dheevatsa Mudigere": "Intel Labs", "KiJung Yoon": "Rice University", "Bjoern Andres": "MPI for Informatics", "Hyun Oh Song": "Seoul National University", "Hanlin Tang": "University of Rochester", "Max Igl": "University of Oxford", "Nikita Doikov": "National Research University Higher School of Economics", "Carrie Cai": "", "Sriram Somasundaram": "University of Southern California", "Ning Chen": "", "Sam Ritter": "DeepMind", "Frank Hutter": "University of Freiburg", "Diederik Roijers": "VUB", "Xiangru Lian": "University of Rochester", "Sung Ju Hwang": "KAIST", "Jiashi Feng": "National University of Singapore", "Yingzhen Yang": "University of Illinois at Urbana-Champaign", "Matt Taddy": "MICROSOFT", "Kevin Tian": "Stanford University", "Srikumar Ramalingam": "University of Utah", "Zhuoran Yang": "Princeton University", "Eric Wong": "Carnegie Mellon University", "Alexandros Karatzoglou": "Telefonica", "Yizhen Zhang": "", "Surbhi Goel": "University of Texas at Austin", "Shuai Zheng": "Hong Kong University of Science and Technology", "Lukas Balles": "Max Planck Institute for Intelligent Systems", "Stephan G\u00fcnnemann": "Technical University of Munich", "John Fisher": "MIT", "Guillaume R Obozinski": "Ecole des Ponts - ParisTech", "Netanel Raviv": "California Institute of Technology", "Behnam Neyshabur": "New York University", "Heinrich Jiang": "Google", "Sima Behpour": "University of Illinois at Chicago", "Tie-Yan Liu": "Microsoft Research Asia", "Jeff Dean": "Google Brain", "Dongruo Zhou": "University of Virginia", "Yiming Ying": "SUNY Albany", "Marine LE MORVAN": "Mines Paristech", "Moustapha Cisse": "Google", "Yuval Kluger": "Yale School of Medicine", "Arian Maleki": "Columbia", "Tianhao Wang": "University of Science and Technology of China", "Mingsheng Long": "Tsinghua University", "Christian Walder": "Data61, the Australian National University", "Tom Ryder": "Newcastle University", "XUDONG LI": "Princeton Univerisity", "Ron Weiss": "Google Brain", "Dongwoo Kim": "The Australian National University", "Omer Reingold": "Stanford University", "Jukka Intosalmi": "Aalto University", "Arnu Pretorius": "Stellenbosch University", "Robert Schapire": "Microsoft Research", "Chiru Bhattacharyya": "Indian Institute of Science", "Philipp Moritz": "UC Berkeley", "Ye Jia": "Google", "Massih-Reza Amini": "Univ. Grenoble Alpes", "Tijana Zrnic": "University of California, Berkeley", "Carola-Bibiane Sch\u00f6nlieb": "University of Cambridge", "Kevin Smith": "KTH Royal Institute of Technology", "Vasilis Syrgkanis": "Microsoft Research", "Weiyao Wang": "Duke", "Xingguo Li": "University of Minnesota", "Lalit Jain": "University of Washington", "Lei Han": "Tencent AI Lab", "Amy Zhang": "Facebook AI Research", "Adam Trischler": "Microsoft Research", "John Quan": "DeepMind", "Ken Stanley": "Uber AI Labs & University of Central Florida", "Zhi-Hua Zhou": "Nanjing University", "Robert Ganian": "TU Wien", "Kejun Huang": "University of Minnesota", "Atsushi Nitanda": "The University of Tokyo / RIKEN", "Nico G\u00f6rnitz": "TU Berlin", "Zequn Jie": "Tencent AI Lab", "Sophie Guo": "Guo", "Ann Now\u00e9": "Vrije Universiteit Brussel", "Bing Su": "Institute of Software Chinese Academy of Sciences", "Michael Jordan": "UC Berkeley", "Rajesh Ranganath": "New York University", "Tamara Broderick": "MIT", "Miroslav Dudik": "Microsoft Research", "SHIYU LIANG": "UIUC", "Konrad Zolna": "Universite de Montreal, Jagiellonian University", "xaq S Pitkow": "Baylor College of Medicine / Rice University", "Sanjay Purushotham": "University of Southern California", "Le Song": "Georgia Institute of Technology", "Dimitar Dimitrov": "ETH Zurich", "Minyoung Kim": "SeoulTech, Rutgers University", "Hao Lu": "Princeton University", "Stratis Gavves": "University of Amsterdam", "Steve Kroon": "Stellenbosch University", "University of Wisconsin David Page": "University of Wisconsin, Madison", "Alexandre Garcia": "Telecom Paristech", "Henrik Mannerstr\u00f6m": "Aalto University", "Zichao Long": "Peking University", "Kevin Jamieson": "University of Washington", "MANSOOR I YOUSEFI": "Telecom ParisTech", "Kenji Doya": "Okinawa Institute of Science and Technology", "Luca Daniel": "MIT", "Mikayel Samvelyan": "Russian-Armenian University", "Zhouyuan Huo": "University of Pittsburgh", "Lester Mackey": "Microsoft Research", "Finale Doshi-Velez": "Harvard University", "Lin Xiao": "Microsoft Research", "Lionel Martin": "EPFL", "Matthew Streeter": "Google", "Yichong Xu": "Carnegie Mellon University", "Oleksandr Shchur": "Technical University of Munich", "Boris Sharchilev": "Yandex", "Gad A Cohen": "Hebrew University", "Ehsan Imani": "University of Alberta", "Yinyu Ye": "", "Vlad Mnih": "Google Deepmind", "Seong-Whan Lee": "Korea University", "Iain Murray": "University of Edinburgh", "Vijay Vasudevan": "Google", "Nal Kalchbrenner": "DeepMind", "Adil El Mesaoudi-Paul": "University of Paderborn", "Michael Veale": "UCL", "Animashree Anandkumar": "Caltech", "Lukasz Kaiser": "Google", "Jean Honorio": "Purdue University", "Charlie Dickens": "Alan Turing Institute & University of Warwick", "Dan Amir": "Hebrew University of Jerusalem", "Sergey Ivanov": "Skoltech & Criteo", "Bo Zhang": "Tsinghua University", "Francesco Locatello": "MPI - ETH", "Huan Xu": "Georgia Tech", "Steffen Udluft": "Siemens AG", "Qiang Yang": "Hong Kong UST", "Li Fei-Fei": "Stanford University & Google", "Corentin Tallec": "INRIA", "Suman Ravuri": "DeepMind", "Danilo Macci\u00f2": "", "Yves Grandvalet": "CNRS/UTC", "Roger Grosse": "University of Toronto and Vector Institute", "Ulrike von Luxburg": "University of T\u00fcbingen", "Aurko Roy": "Google Brain", "Joel Shor": "Google", "Honglak Lee": "Google / U. Michigan", "Herve Glotin": "Universite de Toulon", "Eric Battenberg": "", "Kevin Winner": "University of Massachusetts, Amherst", "Ricardo Henao": "Duke University", "Chao Tao": "Indiana University Bloomington", "Yanjun Qi": "University of Virginia", "Feilx Hill": "Deepmind", "Rob Cornish": "Oxford", "Daniele Calandriello": "INRIA Lille", "Clint Ho": "Imperial College London", "Martin Schiegg": "Bosch Center for AI (BCAI)", "Yu-Xiang Wang": "Amazon / UCSB", "Tengfei Zhou": "Zhejiang University", "Shengming Luo": "CMU", "Pieter-Jan Kindermans": "Google", "David Donoho": "Stanford University", "Daniel Simpson": "University of Toronto", "Sanmi Koyejo": "University of Illinois at Urbana-Champaign", "Max Guangyu Li": "University of Southern California", "Yue Wang": "Rice University", "Mark McLeod": "University of Oxford", "Heiga Zen": "", "Wilson Ye Chen": "University of Technology Sydney", "cbajaj bajaj": "University of Texas at Austin", "Zhenxiao Liang": "Tsinghua University", "Michael Natole Jr": "University at Albany", "Ti John": "PROWLER.io", "Minmin Chen": "Google research", "Ji Xu": "Columbia University", "Kaizheng Wang": "Princeton University", "Shipra Agrawal": "Columbia University", "Carey Priebe": "Johns Hopkins University", "Andrew Rabinovich": "Magic Leap, Inc.", "Ilias Diakonikolas": "USC", "Yuanzhi Li": "Princeton University", "George Tucker": "Google Brain", "Zhibing Zhao": "Rensselaer Polytechnic Institute", "Anitha Kannan": "Curai", "Silvio Lattanzi": "Google Zurich", "Li Gu": "University of Toronto", "Alex Dimakis": "UT Austin", "Matthew Mirman": "ETH Z\u00fcrich", "Marco Baroni": "Facebook Artificial Intelligence Research", "Yoram Singer": "Google", "Hyunjung Shim": "Yonsei University", "Patrick Schwab": "ETH Zurich", "Enhong Chen": "University of Science and Technology of China", "A\u00e4ron van den Oord": "Google Deepmind", "Arshdeep Sekhon": "University of Virginia", "Olivier Fercoq": "", "Felix Xinnan Yu": "Google AI", "Jiaxin Shi": "Tsinghua University", "Guilherme Franca": "Johns Hopkins University", "RJ-Skerry Ryan": "", "Yewen Pu": "MIT", "Eric Xing": "Carnegie Mellon University", "Stefan Schaal": "University of Southern California", "Alessandro Sordoni": "Microsoft Research", "Sainbayar Sukhbaatar": "NYU", "Nikhil Mishra": "", "Yong Yu": "Shanghai Jiao Tong University", "Sai Rajeswar": "University of Montreal", "Nicolas Usunier": "Facebook AI Research", "Brandon Reagen": "Harvard University", "Yazhe Li": "Deepmind", "Ruiqi Zhong": "Columbia University in the City of New York", "Esther Rolf": "UC Berkeley", "Junpei Komiyama": "U-Tokyo", "Ghazal Fazelnia": "Columbia University", "Akifumi Okuno": "Kyoto University / RIKEN AIP", "Ingmar Posner": "University of Oxford", "Luis C Cobo": "DeepMind", "Aditya Grover": "Stanford University", "Ken-ichi Kawarabayashi": "National Institute of Informatics", "Mitchell Stern": "UC Berkeley", "Pan Xu": "University of Virginia", "Yu Xuan Liu": "University of California, Berkeley", "Wenyuan Zeng": "University of Toronto, Uber ATG", "Tom Ward": "DeepMind", "Takanori Maehara": "RIKEN AIP", "Roi Weiss": "WeizmannInstitute", "Samaras Dimitris": "Stony Brook University", "Philipp Hennig": "University of T\u00fcbingen", "Mehmet Fatih Sahin": "Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne", "Zhongming Liu": "Purdue University", "Abhishek Bansal": "IBM Research", "May Wang": "Georgia Institute of Technology", "R Devon Hjelm": "MILA", "Morino Pan": "Fudan University", "IHPC Shuji Hao": "IHPC, A*STAR", "Hongyuan Zha": "Georgia Institute of Technology", "Joe Marino": "Caltech", "Mingyuan Zhou": "University of Texas at Austin", "Junhong Lin": "EPFL", "Xinhua Zhang": "University of Illinois at Chicago", "Ryutaro Tanno": "University College London", "Alex Smola": "Amazon", "Alexandr Andoni": "", "Brian Williamson": "University of Washington", "Sebastian Stich": "EPFL", "Lydia T. Liu": "University of California Berkeley", "Michael Kearns": "University of Pennsylvania", "Gregory Naisat": "The University of Chicago", "Andy Palaniappan": "UC Berkeley", "Vikas Sindhwani": "Google", "Hieu Pham": "Carnegie Mellon University", "Naonori Kakimura": "Keio University", "Mehryar Mohri": "Courant Institute and Google Research", "Hanna Wallach": "Microsoft Research", "Hajime Shimao": "Purdue University", "Mirco Mutti": "Politecnico di Milano", "Luca Franceschi": "Istituto Italiano di Tecnologia - University College London", "Aristide Baratin": "University of Montreal", "Christopher Olah": "Google Brain", "Amartya Sanyal": "University of Oxford", "Timon Gehr": "ETH Zurich", "Rhicheek Patra": "EPFL", "Teodor Vanislavov Marinov": "Johns Hopkins University", "Tomohiro Sonobe": "National Institute of Informatics", "Orecchia Lorenzo": "Boston", "Theo Weber": "DeepMind", "Grigory Yaroslavtsev": "Indiana University", "Konstantinos Kamnitsas": "Imperial College London", "University of California Xuanqing Liu": "University of California, Davis", "Kyle Helfrich": "University of Kentucky", "Avinatan Hasidim": "Google", "Ian Osband": "Google DeepMind", "Shuicheng Yan": "Qihoo/360", "Yuxin Chen": "Princeton University", "Prateek Jain": "Microsoft Research", "Marc P Deisenroth": "Imperial College London and PROWLER.io", "Qianxiao Li": "Institute of High Performance Computing, A*STAR, Singapore", "Xiaoyu Lu": "University of Oxford", "Vivek Srikumar": "University of Utah", "Han Liu": "Northwestern", "Zibin Zheng": "", "Rob Vandermeulen": "TU Kaiserslautern", "Kilian Weinberger": "Cornell University", "Cong Ma": "Princeton University", "Chris De Sa": "Cornell", "ALEXANDROS GEORGOGIANNIS": "TECHNICAL UNIVERSITY OF CRETE", "Steffen Rendle": "Google", "Yixuan Li": "Facebook Inc", "John Langford": "MSR", "Alan Fern": "Oregon State University", "Philip Thomas": "University of Massachusetts Amherst", "Zeb Kurth-Nelson": "DeepMind", "Fei Tian": "Microsoft Research", "Marco Baity-Jesi": "Columbia University", "Timo Aila": "NVIDIA", "Marta Garnelo": "DeepMind", "Tatsunori Hashimoto": "Stanford", "Andrew Gelman": "Columbia University", "Gal Yona": "Weizmann Institute of Science", "Zhe Gan": "Duke University", "Yuwen Xiong": "Uber ATG / University of Toronto", "Arpit Agarwal": "University of Pennsylvania", "Tianbao Yang": "The University of Iowa", "Michael Neunert": "Google DeepMind", "Nathan Fenner": "Afresh Technologies", "Ellen Vitercik": "Carnegie Mellon University", "Kunal Talwar": "Google", "Andreas Geiger": "MPI-IS and University of Tuebingen", "Marius Kloft": "TU Kaiserslautern", "Niazadeh Niazadeh": "Stanford University", "Lisa Lee": "Carnegie Mellon University", "Debora Sujono": "University of Massachusetts Amherst", "Ashwin Kalyan": "Georgia Tech", "Francis Song": "DeepMind", "Seth V Neel": "University of Pennsylvania", "Dmitrii Ostrovskii": "INRIA", "Christopher Yau": "University of Birmingham", "Peng Sun": "Tencent AI Lab", "Jakob Foerster": "University of Oxford", "Phuc Nguyen": "UC Irvine", "James Hensman": "PROWLER.io", "Jun Han": "Dartmouth College", "Peter Jin": "UC Berkeley", "Johanni Brea": "EPFL", "Wissam Siblini": "Orange Labs", "Zilu Zhang": "Peking University", "Ming Zhou": "Shanghai Jiao Tong University", "Michael Mahoney": "UC Berkeley", "andrew warrington": "University of Oxford", "Markus Heinonen": "Aalto University", "Keisuke Yamazaki": "National Institute of Advanced Industrial Science and Technology", "Alon Cohen": "Google Inc.", "Luisa Zintgraf": "University of Oxford", "Junhyuk Oh": "University of Michigan", "Arman Sharifi Kolarijani": "Delft University of Technology", "Guoyin Wang": "Duke University", "Peggy Peissig": "Marshfield Clinic Research Foundation", "Alexander Ku": "UC Berkeley", "Qi Lei": "University of Texas at Austin", "Dale Schuurmans": "University of Alberta", "Frank Meyer": "Orange Labs Lannion", "University of California James Sharpnack": "University of California, Davis", "Nevan Wichers": "Google", "Razvan Pascanu": "DeepMind", "Daniel LeJeune": "Rice University", "Kannan Ramchandran": "UC Berkeley", "Martin Vechev": "ETH Zurich", "Thomas Kerdreux": "INRIA", "Eugenio Bargiacchi": "Vrije Universiteit Brussel", "Sander Dieleman": "DeepMind", "Jaesik Choi": "Ulsan National Institute of Science and Technology", "Jiayu Yao": "Harvard University", "Nicholas Carlini": "University of California, Berkeley", "Tiago Ramalho": "DeepMind", "Liwei Wang": "Peking University", "Georgios Damaskinos": "EPFL", "Ian Davidson": "UC Davis", "C\u00e9dric Colas": "Inria", "Zihang He": "Tsinghua University", "S. M. Ali Eslami": "DeepMind", "Edwin Bonilla": "UNSW", "Jason Lee": "University of Southern California", "Siyuan Qi": "UCLA", "Tian Gao": "IBM Research", "Emanuela Keller": "University Hospital Zurich", "Maithra Raghu": "Google Brain / Cornell University", "My Thai": "University of Florida", "Tal Friedman": "UCLA", "Nicolas Vayatis": "CMLA, ENS Paris Saclay", "Konstantin Mishchenko": "King Abdullah University of Science & Technology (KAUST)"}]