jmlr_2015.json

[{"Statistical decision making for optimal budget allocation in crowd labeling": ["Xi Chen", "Qihang Lin", "Dengyong Zhou"], "Simultaneous pursuit of sparseness and rank structures for matrix decomposition": ["Qi Yan", "Jieping Ye", "Xiaotong Shen"], "Statistical topological data analysis using persistence landscapes": ["Peter Bubenik"], "Links between multiplicity automata, observable operator models and predictive state representations: a unified learning framework": ["Michael Thon", "Herbert Jaeger"], "SAMOA: scalable advanced massive online analysis": ["Gianmarco De Francisci Morales", "Albert Bifet"], "Online learning via sequential complexities": ["Alexander Rakhlin", "Karthik Sridharan", "Ambuj Tewari"], "Learning transformations for clustering and classification": ["Qiang Qiu", "Guillermo Sapiro"], "Multi-layered gesture recognition with Kinect": ["Feng Jiang", "Shengping Zhang", "Shen Wu", "Yang Gao", "Debin Zhao"], "Multimodal gesture recognition via multiple hypotheses rescoring": ["Vassilis Pitsikalis", "Athanasios Katsamanis", "Stavros Theodorakis", "Petros Maragos"], "An asynchronous parallel stochastic coordinate descent algorithm": ["Ji Liu", "Stephen J. Wright", "Christopher R\u00e9", "Victor Bittorf", "Srikrishna Sridhar"], "Geometric intuition and algorithms for Ev-SVM": ["\u00c0lvaro Barbero", "Akiko Takeda", "Jorge L\u00f3pez"], "Composite self-concordant minimization": ["Quoc Tran-Dinh", "Anastasios Kyrillidis", "Volkan Cevher"], "Network granger causality with inherent grouping structure": ["Sumanta Basu", "Ali Shojaie", "George Michailidis"], "Iterative and active graph clustering using trace norm minimization without cluster size constraints": ["Nir Ailon", "Yudong Chen", "Huan Xu"], "A classification module for genetic programming algorithms in JCLEC": ["Alberto Cano", "Jos\u00e9 Mar\u00eda Luna", "Amelia Zafra", "Sebasti\u00e1n Ventura"], "AD3: alternating directions dual decomposition for MAP inference in graphical models": ["Andr\u00e9 F. T. Martins", "M\u00e1rio A. T. Figueiredo", "Pedro M. Q. Aguiar", "Noah A. Smith", "Eric P. Xing"], "Introducing CURRENNT: the Munich open-source CUDA recurrent neural network toolkit": ["Felix Weninger", "Johannes Bergmann", "Bj\u00f6rn Schuller"], "The flare package for high dimensional linear regression and precision matrix estimation in R": ["Xingguo Li", "Tuo Zhao", "Xiaoming Yuan", "Han Liu"], "Regularized M-estimators with nonconvexity: statistical and algorithmic theory for local optima": ["Po-Ling Loh", "Martin J. Wainwright"], "Generalized hierarchical kernel learning": ["Pratik Jawanpuria", "Jagarlapudi Saketha Nath", "Ganesh Ramakrishnan"], "Discrete restricted Boltzmann machines": ["Guido Mont\u00fafar", "Jason Morton"], "Evolving GPU machine code": ["Cleomar Pereira Da Silva", "Douglas Mota Dias", "Cristiana Bentes", "Marco Aur\u00e9lio Cavalcanti Pacheco", "Leandro Fontoura Cupertino"], "A compression technique for analyzing disagreement-based active learning": ["Yair Wiener", "Steve Hanneke"], "Response-based approachability with applications to generalized no-regret problems": ["Andrey Bernstein", "Nahum Shimkin"], "Strong consistency of the prototype based clustering in probabilistic space": ["Vladimir Nikulin"], "Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm": ["Pascal Germain", "Alexandre Lacasse", "Fran\u00e7ois Laviolette", "Mario Marchand", "Jean-Francis Roy"], "A statistical perspective on algorithmic leveraging": ["Ping Ma", "Michael W. Mahoney", "Bin Yu"], "Distributed matrix completion and robust factorization": ["Lester Mackey", "Ameet Talwalkar", "Michael I. Jordan"], "Combined l1 and greedy l0 penalized least squares for linear model selection": ["Piotr Pokarowski", "Jan Mielniczuk"], "Learning with the maximum correntropy criterion induced losses for regression": ["Yunlong Feng", "Xiaolin Huang", "Lei Shi", "Yuning Yang", "Johan A. K. Suykens"], "Joint estimation of multiple precision matrices with common structures": ["Wonyul Lee", "Yufeng Liu"], "Lasso screening rules via dual polytope projection": ["Jie Wang", "Peter Wonka", "Jieping Ye"], "Fast cross-validation via sequential testing": ["Tammo Krueger", "Danny Panknin", "Mikio Braun"], "Learning the structure and parameters of large-population graphical games from behavioral data": ["Jean Honorio", "Luis Ortiz"], "Local identification of overcomplete dictionaries": ["Karin Schnass"], "Encog: library of interchangeable machine learning models for Java and C#": ["Jeff Heaton"], "Perturbed message passing for constraint satisfaction problems": ["Siamak Ravanbakhsh", "Russell Greiner"], "Learning sparse low-threshold linear classifiers": ["Sivan Sabato", "Shai Shalev-Shwartz", "Nathan Srebro", "Daniel Hsu", "Tong Zhang"], "Learning equilibria of games via payoff queries": ["John Fearnley", "Martin Gairing", "Paul W. Goldberg", "Rahul Savani"], "Rationality, optimism and guarantees in general reinforcement learning": ["Peter Sunehag", "Marcus Hutter"], "The algebraic combinatorial approach for low-rank matrix completion": ["Franz J. Kir\u00e1ly", "Louis Theran", "Ryota Tomioka"], "A comprehensive survey on safe reinforcement learning": ["Javier Garc\u00eda", "Fernando Fern\u00e1ndez"], "Second-order non-stationary online learning for regression": ["Edward Moroshko", "Nina Vaits", "Koby Crammer"], "A finite sample analysis of the Naive Bayes classifier": ["Daniel Berend", "Aryeh Kontorovich"], "Flexible high-dimensional classification machines and their asymptotic properties": ["Xingye Qiao", "Lingsong Zhang"], "RLPy: a value-function-based reinforcement learning framework for education and research": ["Alborz Geramifard", "Christoph Dann", "Robert H. Klein", "William Dabney", "Jonathan P. How"], "Calibrated multivariate regression with application to neural semantic basis discovery": ["Han Liu", "Lie Wang", "Tuo Zhaoy"], "Bayesian nonparametric crowdsourcing": ["Pablo G. Moreno", "Antonio Art\u00e9s-Rodr\u00edguez", "Yee Whye Teh", "Fernando Perez-Cruz"], "Approximate modified policy iteration and its application to the game of Tetris": ["Bruno Scherrer", "Mohammad Ghavamzadeh", "Victor Gabillon", "Boris Lesner", "Matthieu Geist"], "Preface to this special issue": ["Alex Gammerman", "Vladimir Vovk"], "V-matrix method of solving statistical inference problems": ["Vladimir Vapnik", "Rauf Izmailov"], "Batch learning from logged bandit feedback through counterfactual risk minimization": ["Adith Swaminathan", "Thorsten Joachims"], "Optimal estimation of low rank density matrices": ["Vladimir Koltchinskii", "Dong Xia"], "Fast rates in statistical and online learning": ["Tim Van Erven", "Peter D. Gr\u00fcnwald", "Nishant A. Mehta", "Mark D. Reid", "Robert C. Williamson"], "On the asymptotic normality of an estimate of a regression functional": ["L\u00e1szl\u00f3 Gy\u00f6rfi", "Harro Walk"], "Sharp oracle bounds for monotone and convex regression through aggregation": ["Pierre C. Bellec", "Alexandre B. Tsybakov"], "Exceptional rotations of random graphs: a VC theory": ["Louigi Addario-Berry", "Shankar Bhamidi", "S\u00e9bastien Bubeck", "Luc Devroye", "G\u00e1bor Lugosi", "Roberto Imbuzeiro Oliveira"], "Semi-supervised interpolation in an anticausal learning scenario": ["Dominik Janzing", "Bernhard Sch\u00f6lkopf"], "Towards an axiomatic approach to hierarchical clustering of measures": ["Philipp Thomann", "Ingo Steinwart", "Nico Schmid"], "Predicting a switching sequence of graph labelings": ["Mark Herbster", "Stephen Pasteris", "Massimiliano Pontil"], "Learning using privileged information: similarity control and knowledge transfer": ["Vladimir Vapnik", "Rauf Izmailov"], "Alexey Chervonenkis's bibliography: introductory comments": ["Alex Gammerman", "Vladimir Vovk"], "Alexey Chervonenkis's bibliography": ["Alex Gammerman", "Vladimir Vovk"], "Photonic delay systems as machine learning implementations": ["Michiel Hermans", "Miguel C. Soriano", "Joni Dambre", "Peter Bienstman", "Ingo Fischer"], "On linearly constrained minimum variance beamforming": ["Jian Zhang", "Chao Liu"], "Constraint-based causal discovery from multiple interventions over overlapping variable sets": ["Sofia Triantafillou", "Ioannis Tsamardinos"], "Existence and uniqueness of proper scoring rules": ["Evgeni Y. Ovcharov"], "Adaptive strategy for stratified Monte Carlo sampling": ["Alexandra Carpentier", "Remi Munos", "Andr\u00e1s Antos"], "Concave penalized estimation of sparse Gaussian Bayesian networks": ["Bryon Aragam", "Qing Zhou"], "Agnostic insurability of model classes": ["Narayana Santhanam", "Venkat Anantharam"], "Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies": ["Kazuho Watanabe", "Teemu Roos"], "Multiclass learnability and the ERM principle": ["Amit Daniely", "Sivan Sabato", "Shai Ben-David", "Shai Shalev-Shwartz"], "Geometry and expressive power of conditional restricted Boltzmann machines": ["Guido Mont\u00fafar", "Nihat Ay", "Keyan Ghazi-Zahedi"], "From dependency to causality: a machine learning approach": ["Gianluca Bontempi", "Maxime Flauder"], "The Libra toolkit for probabilistic models": ["Daniel Lowd", "Amirmohammad Rooshenas"], "Complexity of equivalence and learning for multiplicity tree automata": ["Ines Maru\u0161ic", "James Worrell"], "Bayesian nonparametric covariance regression": ["Emily B. Fox", "David B. Dunson"], "A general framework for fast stagewise algorithms": ["Ryan J. Tibshirani"], "Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs": ["Yangbo He", "Jinzhu Jia", "Bin Yu"], "pyGPs: a Python library for Gaussian process regression and classification": ["Marion Neumann", "Shan Huang", "Daniel E. Marthaler", "Kristian Kersting"], "Derivative estimation based on difference sequence via locally weighted least squares regression": ["Wen Wu Wang", "Lu Lin"], "When are overcomplete topic models identifiable? uniqueness of tensor tucker decompositions with structured sparsity": ["Animashree Anandkumar", "Daniel Hsu", "Majid Janzamin", "Sham Kakade"], "Absent data generating classifier for imbalanced class sizes": ["Arash Pourhabib", "Bani K. Mallick", "Yu Ding"], "Decision boundary for discrete Bayesian network classifiers": ["Gherardo Varando", "Concha Bielza", "Pedro Larra\u00f1aga"], "A view of margin losses as regularizers of probability estimates": ["Hamed Masnadi-Shirazi", "Nuno Vasconcelos"], "Online tensor methods for learning latent variable models": ["Furong Huang", "U. N. Niranjan", "Mohammad Umar Hakeem", "Animashree Anandkumar"], "Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior": ["Debdeep Pati", "Anirban Bhattacharya", "Guang Cheng"], "CEKA: a tool for mining the wisdom of crowds": ["Jing Zhang", "Victor S. Sheng", "Bryce A. Nicholson", "Xindong Wu"], "Linear dimensionality reduction: survey, insights, and generalizations": ["John P. Cunningham", "Zoubin Ghahramani"], "The Randomized Causation Coefficient": ["David Lopez-Paz", "Krikamol Muandet", "Benjamin Recht"], "Optimality of Poisson processes intensity learning with Gaussian processes": ["Alisa Kirichenko", "Harry Van Zanten"], "Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013": ["Chun-Liang Li", "Yu-Chuan Su", "Ting-Wei Lin", "Cheng-Hao Tsai", "Wei-Cheng Chang", "Kuan-Hao Huang", "Tzu-Ming Kuo", "Shan-Wei Lin", "Young-San Lin", "Yu-Chen Lu", "Chun-Pai Yang", "Cheng-Xia Chang", "Wei-Sheng Chin", "Yu-Chin Juan", "Hsiao-Yu Tung", "Jui-Pin Wang", "Cheng-Kuang Wei", "Felix Wu", "Tu-Chun Yin", "Tong Yu", "Yong Zhuang", "Shou-De Lin", "Hsuan-Tien Lin", "Chih-Jen Lin"], "Comparing hard and overlapping clusterings": ["Danilo Horta", "Ricardo J. G. B. Campello"], "Completing any low-rank matrix, provably": ["Yudong Chen", "Srinadh Bhojanapalli", "Sujay Sanghavi", "Rachel Ward"], "Eigenwords: spectral word embeddings": ["Paramveer S. Dhillon", "Dean P. Foster", "Lyle H. Ungar"], "Discrete reproducing kernel Hilbert spaces: sampling and distribution of Dirac-masses": ["Palle Jorgensen", "Feng Tian"], "A direct estimation of high dimensional stationary vector autoregressions": ["Fang Han", "Huanran Lu", "Han Liu"], "Global convergence of online limited memory BFGS": ["Aryan Mokhtari", "Alejandro Ribeiro"], "On semi-supervised linear regression in covariate shift problems": ["Kenneth Joseph Ryan", "Mark Vere Culp"], "Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery": ["Alexander Statnikov", "Sisi Ma", "Mikael Henaff", "Nikita Lytkin", "Efstratios Efstathiadis", "Eric R. Peskin", "Constantin F. Aliferis"], "Plug-and-play dual-tree algorithm runtime analysis": ["Ryan R. Curtin", "Dongryeol Lee", "William B. March", "Parikshit Ram"], "Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates": ["Yuchen Zhang", "John Duchi", "Martin Wainwright"], "Learning theory of randomized Kaczmarz algorithm": ["Junhong Lin", "Ding-Xuan Zhou"], "Matrix completion and low-rank SVD via fast alternating least squares": ["Trevor Hastie", "Rahul Mazumder", "Jason D. Lee", "Reza Zadeh"], "On the inductive bias of dropout": ["David P. Helmbold", "Philip M. Long"], "Agnostic learning of disjunctions on symmetric distributions": ["Vitaly Feldman", "Pravesh Kothari"], "SnFFT: a Julia toolkit for Fourier analysis of functions over permutations": ["Gregory Plumb", "Deepti Pachauri", "Risi Kondor", "Vikas Singh"], "The sample complexity of learning linear predictors with the squared loss": ["Ohad Shamir"], "Minimax analysis of active learning": ["Steve Hanneke"], "Convergence rates for persistence diagram estimation in topological data analysis": ["Fr\u00e9d\u00e9ric Chazal", "Marc Glisse", "Catherine Labru\u00e8re", "Bertrand Michel"], "Supervised learning via Euler's Elastica models": ["Tong Lin", "Hanlin Xue", "Ling Wang", "Bo Huang", "Hongbin Zha"], "Learning to identify concise regular expressions that describe email campaigns": ["Paul Prasse", "Christoph Sawade", "Niels Landwehr", "Tobias Scheffer"], "Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards": ["Junya Honda", "Akimichi Takemura"], "Condition for perfect dimensionality recovery by variational Bayesian PCA": ["Shinichi Nakajima", "Ryota Tomioka", "Masashi Sugiyama", "S. Derin Babacan"], "Graphical models via univariate exponential family distributions": ["Eunho Yang", "Pradeep Ravikumar", "Genevera I. Allen", "Zhandong Liu"], "Marginalizing stacked linear denoising autoencoders": ["Minmin Chen", "Kilian Q. Weinberger", "Zhixiang Xu", "Fei Sha"], "PAC optimal MDP planning with application to invasive species management": ["Majid Alkaee Taleghan", "Thomas G. Dietterich", "Mark Crowley", "Kim Hall", "H. Jo Albers"], "Partykit: a modular toolkit for recursive partytioning in R": ["Torsten Hothorn", "Achim Zeileis"]}, {"Statistical decision making for optimal budget allocation in crowd labeling": ["algorithms", "budget allocation", "crowdsourcing", "design", "dynamic programming", "experimentation", "expert systems", "information systems applications", "machine learning", "markov decision process", "measurement", "optimistic knowledge gradient", "performance", "statistical graphics", "statistical paradigms"], "Simultaneous pursuit of sparseness and rank structures for matrix decomposition": ["algorithms", "blockwise decent", "computations on matrices", "design", "experimentation", "expert systems", "information systems applications", "machine learning", "matrix decomposition", "measurement", "nonconvex minimization", "performance", "structure pursuit"], "Statistical topological data analysis using persistence landscapes": ["algorithms", "design", "experimentation", "expert systems", "information systems applications", "machine learning", "measurement", "performance", "persistence landscape", "persistent homology", "statistical graphics", "statistical paradigms", "statistical topology", "topological data analysis", "topological summary"], "Links between multiplicity automata, observable operator models and predictive state representations: a unified learning framework": ["algorithms", "design", "experimentation", "expert systems", "formal languages and automata theory", "hidden markov models", "information systems applications", "machine learning", "measurement", "multiplicity automata", "observable operator models", "performance", "predictive state representations", "spectral learning algorithms"], "SAMOA: scalable advanced massive online analysis": ["algorithms", "classification", "clustering", "data streams", "design", "distributed systems", "experimentation", "expert systems", "information systems applications", "interactive computation", "machine learning", "machine learning", "measurement", "online learning algorithms", "online learning theory", "performance", "regression", "toolbox"], "Online learning via sequential complexities": ["algorithms", "design", "experimentation", "expert systems", "information systems applications", "interactive computation", "machine learning", "measurement", "online learning", "online learning algorithms", "online learning theory", "performance", "regret minimization", "sequential complexities"], "Learning transformations for clustering and classification": ["algorithms", "classification", "classification and regression trees", "design", "experimentation", "expert systems", "feature learning", "information systems applications", "low-rank transformation", "machine learning", "measurement", "nuclear norm", "performance", "subspace clustering", "supervised learning by classification"], "Multi-layered gesture recognition with Kinect": ["algorithms", "computer vision", "design", "dynamic time warping", "experimentation", "expert systems", "gesture recognition", "information systems applications", "kinect", "linguistic characters", "machine learning", "measurement", "multi-layered classification", "object recognition", "performance", "principle motion", "scene understanding"], "Multimodal gesture recognition via multiple hypotheses rescoring": ["activity detection", "algorithms", "computer vision", "design", "experimentation", "expert systems", "hmms", "information systems applications", "machine learning", "measurement", "multimodal fusion", "multimodal gesture recognition", "object recognition", "performance", "scene understanding", "speech recognition"], "An asynchronous parallel stochastic coordinate descent algorithm": ["algorithms", "asynchronous parallel optimization", "design", "experimentation", "expert systems", "information systems applications", "machine learning", "measurement", "performance", "stochastic control and optimization", "stochastic coordinate descent"], "Geometric intuition and algorithms for Ev-SVM": ["algorithms", "classification", "computational geometry", "design", "ev-svm", "experimentation", "expert systems", "information systems applications", "machine learning", "measurement", "nearest point problem", "performance", "randomness, geometry and discrete structures", "reduced convex hulls", "svm"], "Composite self-concordant minimization": ["algorithms", "composite minimization", "design", "experimentation", "expert systems", "graph learning", "information systems applications", "machine learning", "mathematical optimization", "measurement", "performance", "proximal-gradient/newton method", "self-concordance", "sparse convex optimization"], "Network granger causality with inherent grouping structure": ["algorithms", "design", "experimentation", "expert systems", "granger causality", "group lasso", "high dimensional networks", "information systems applications", "machine learning", "measurement", "network flows", "panel vector autoregression model", "performance", "thresholding"], "Iterative and active graph clustering using trace norm minimization without cluster size constraints": ["active clustering", "algorithms", "cluster analysis", "community detection", "convex optimization", "design", "experimentation", "expert systems", "graph clustering", "graph theory", "information systems applications", "machine learning", "measurement", "performance", "planted partition model", "stochastic block model"], "A classification module for genetic programming algorithms in JCLEC": ["algorithms", "classification", "classification and regression trees", "design", "evolutionary algorithms", "experimentation", "expert systems", "genetic programming", "information systems applications", "jclec", "machine learning", "measurement", "performance", "supervised learning by classification"], "AD3: alternating directions dual decomposition for MAP inference in graphical models": ["algorithms", "alternating directions method of multipliers", "design", "dual decomposition", "experimentation", "expert systems", "graph theory", "graphical models", "information systems applications", "machine learning", "map inference", "measurement", "performance"], "Introducing CURRENNT: the Munich open-source CUDA recurrent neural network toolkit": ["algorithms", "cellular neural networks", "deep neural networks", "design", "experimentation", "expert systems", "information systems applications", "long short-term memory", "machine learning", "machine learning theory", "measurement", "neural networks", "parallel computing", "performance", "recurrent neural networks"], "The flare package for high dimensional linear regression and precision matrix estimation in R": ["algorithms", "alternating direction method of multipliers", "canonical correlation analysis", "design", "experimentation", "expert systems", "information systems applications", "machine learning", "measurement", "performance", "regression analysis", "robustness", "sparse linear regression", "sparse precision matrix estimation", "tuning insensitiveness"], "Regularized M-estimators with nonconvexity: statistical and algorithmic theory for local optima": ["algorithms", "design", "experimentation", "expert systems", "high-dimensional statistics", "information systems applications", "m-estimation", "machine learning", "mathematical optimization", "measurement", "model selection", "nonconvex optimization", "nonconvex regularization", "performance"], "Generalized hierarchical kernel learning": ["active set method", "algorithms", "design", "experimentation", "expert systems", "information systems applications", "machine learning", "measurement", "mixed-norm regularization", "multi-task learning", "multiple kernel learning", "performance", "rule ensemble learning"], "Discrete restricted Boltzmann machines": ["distributed representation", "expected dimension", "na\u00efve bayes model", "representational power", "restricted boltzmann machine"], "Evolving GPU machine code": ["genetic programming", "graphics processing units", "machine code"], "A compression technique for analyzing disagreement-based active learning": ["active learning", "pac learning", "sample complexity", "selective prediction", "selective sampling", "sequential design", "statistical learning theory"], "Response-based approachability with applications to generalized no-regret problems": ["approachability", "no-regret algorithms"], "Strong consistency of the prototype based clustering in probabilistic space": ["clustering", "consistency", "probabilistic space"], "Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm": ["ensemble methods", "learning theory", "majority vote", "pac-bayesian theory", "sample compression"], "A statistical perspective on algorithmic leveraging": ["least squares", "leverage scores", "linear regression", "randomized algorithm", "subsampling"], "Distributed matrix completion and robust factorization": ["collaborative filtering", "divide-and-conquer", "matrix completion", "matrix factorization", "parallel and distributed algorithms", "randomized algorithms", "robust matrix factorization", "video surveillance"], "Combined l1 and greedy l0 penalized least squares for linear model selection": ["generalized information criterion", "greedy search", "lasso", "linear model selection", "multi-stage convex relaxation", "penalized least squares"], "Learning with the maximum correntropy criterion induced losses for regression": ["correntropy", "least squares regression", "robust loss function", "robust regression", "statistical learning theory", "the maximum correntropy criterion"], "Joint estimation of multiple precision matrices with common structures": ["covariance matrix", "graphical model", "high dimension", "joint estimation", "precision matrix"], "Lasso screening rules via dual polytope projection": ["dual formulation", "large-scale optimization", "lasso", "polytope projection", "safe screening", "sparse regularization"], "Fast cross-validation via sequential testing": ["cross-validation", "nonparametric methods", "statistical testing"], "Learning the structure and parameters of large-population graphical games from behavioral data": ["behavioral data in strategic settings", "graphical games", "linear influence games", "structure and parameter learning"], "Local identification of overcomplete dictionaries": ["dictionary identification", "dictionary learning", "finite sample size", "k-means", "maximization criterion", "sample complexity", "sparse coding", "sparse component analysis", "sparse representation", "vector quantization"], "Encog: library of interchangeable machine learning models for Java and C#": ["c#", "java", "neural network", "open source software", "support vector machine"], "Perturbed message passing for constraint satisfaction problems": ["belief propagation", "constraint satisfaction problem", "decimation", "gibbs sampling", "message passing", "survey propagation"], "Learning sparse low-threshold linear classifiers": ["empirical risk minimization", "linear classifiers", "monotone disjunctions", "online learning", "uniform convergence"], "Learning equilibria of games via payoff queries": ["approximate nash equilibrium", "bimatrix game", "congestion game", "equilibrium computation", "query complexity"], "Rationality, optimism and guarantees in general reinforcement learning": ["error bounds", "optimality", "optimism", "rationality", "reinforcement learning"], "The algebraic combinatorial approach for low-rank matrix completion": ["algebraic combinatorics", "entry-wise completion", "low-rank matrix completion", "matrix reconstruction"], "A comprehensive survey on safe reinforcement learning": ["reinforcement learning", "risk sensitivity", "safe exploration", "teacher advice"], "Second-order non-stationary online learning for regression": ["non-stationary input", "online learning", "regret bounds"], "A finite sample analysis of the Naive Bayes classifier": ["chernoff-stein lemma", "experts", "hypothesis testing", "measure concentration", "naive bayes", "neyman-pearson lemma"], "Flexible high-dimensional classification machines and their asymptotic properties": ["classification", "fisher consistency", "high-dimensional low-sample size asymptotics", "imbalanced data", "support vector machine"], "RLPy: a value-function-based reinforcement learning framework for education and research": ["empirical evaluation", "open source", "reinforcement learning", "value-function"], "Calibrated multivariate regression with application to neural semantic basis discovery": ["brain activity prediction", "calibration", "high dimension", "low rank", "multivariate regression", "sparsity"], "Bayesian nonparametric crowdsourcing": ["bayesian nonparametrics", "dirichlet process", "gibbs sampling", "hierarchical clustering", "multiple annotators"], "Approximate modified policy iteration and its application to the game of Tetris": ["approximate dynamic programming", "finite-sample analysis", "game of tetris", "markov decision processes", "performance bounds", "reinforcement learning"], "Preface to this special issue": [], "V-matrix method of solving statistical inference problems": ["conditional density", "conditional probability", "data adaptation", "data balancing", "density ratio", "function estimation", "ill-posed problem", "interpolation function", "mutual information", "regression", "reproducing kernel hilbert space", "support vector machines"], "Batch learning from logged bandit feedback through counterfactual risk minimization": ["bandit feedback", "empirical risk minimization", "importance sampling", "propensity score matching", "structured prediction"], "Optimal estimation of low rank density matrices": ["low rank density matrix", "minimax lower bounds", "quantum state tomography"], "Fast rates in statistical and online learning": ["exp-concavity", "fast rates", "mixability", "statistical learning theory", "tsybakov margin condition"], "On the asymptotic normality of an estimate of a regression functional": ["central limit theorem", "nonparametric estimation", "partitioning estimate", "regression functional"], "Sharp oracle bounds for monotone and convex regression through aggregation": ["aggregation", "convex regression", "isotonic regression", "minimax regret", "model misspecification", "shape constraints", "sharp oracle inequalities"], "Exceptional rotations of random graphs: a VC theory": ["chromatic number", "clique number", "connectivity", "random graphs", "vc theory"], "Semi-supervised interpolation in an anticausal learning scenario": ["anticausal learning", "causality", "independence of cause and mechanism", "information geometry", "semi-supervised learning"], "Towards an axiomatic approach to hierarchical clustering of measures": ["axiomatic clustering", "density level set clustering", "hierarchical clustering", "infinite samples clustering", "mixed hausdorff-dimensions"], "Predicting a switching sequence of graph labelings": ["kernel methods", "matrix winnow", "online learning over graphs", "switching"], "Learning using privileged information: similarity control and knowledge transfer": ["classification", "frames", "intelligent teacher", "kernel functions", "knowledge representation", "knowledge transfer", "learning theory", "privileged information", "regression", "similarity control", "similarity functions", "support vector machines", "svm+"], "Alexey Chervonenkis's bibliography: introductory comments": [], "Alexey Chervonenkis's bibliography": [], "Photonic delay systems as machine learning implementations": ["machine learning models", "optical computing", "recurrent neural networks"], "On linearly constrained minimum variance beamforming": ["meg neuroimaging", "source localization and reconstruction", "sparse covariance estimation", "vector-beamforming"], "Constraint-based causal discovery from multiple interventions over overlapping variable sets": ["causal discovery", "causality", "graphical models", "latent variables", "maximal ancestral graphs", "randomized experiments", "semi-markov causal models"], "Existence and uniqueness of proper scoring rules": ["characterisation", "convex analysis", "directional derivative", "entropy", "existence", "g\u00e2teaux derivative", "proper scoring rules", "quasiinterior", "subgradient", "sublinear", "uniqueness"], "Adaptive strategy for stratified Monte Carlo sampling": ["active learning", "adaptive sampling", "bandit theory", "minimax strategies", "stratied monte carlo"], "Concave penalized estimation of sparse Gaussian Bayesian networks": ["bayesian networks", "concave penalization", "coordinate descent", "directed acyclic graphs", "nonconvex optimization"], "Agnostic insurability of model classes": ["insurance, l1 topology of probability distributions over countable sets", "non-parametric approaches", "prediction of quantiles of distributions", "universal compression"], "Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies": ["asymptotic minimax regret", "bayes mixture", "normalized maximum likelihood", "on-line learning", "prediction of individual sequences"], "Multiclass learnability and the ERM principle": ["erm", "multiclass", "sample complexity"], "Geometry and expressive power of conditional restricted Boltzmann machines": ["conditional restricted boltzmann machine", "expected dimension", "kullback-leibler approximation error", "universal approximation"], "From dependency to causality: a machine learning approach": ["causal inference", "information theory", "machine learning"], "The Libra toolkit for probabilistic models": ["inference", "probabilistic graphical models", "structure learning"], "Complexity of equivalence and learning for multiplicity tree automata": ["dag representations of trees", "exact learning", "hankel matrices", "multiplicity tree automata", "polynomial identity testing", "query complexity"], "Bayesian nonparametric covariance regression": ["covariance regression", "dictionary learning", "gaussian process", "latent factor model", "nonparametric bayes", "time series"], "A general framework for fast stagewise algorithms": ["\u03b5-boosting", "forward stagewise regression", "lasso", "regularization paths"], "Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs": ["causality", "directed acyclic graphs", "markov equivalence class", "size distribution"], "pyGPs: a Python library for Gaussian process regression and classification": ["gaussian processes", "python", "regression and classification"], "Derivative estimation based on difference sequence via locally weighted least squares regression": ["biascorrection", "locally weighted least squares", "nonparametric derivative estimation", "symmetric difference sequence", "taylor expansion"], "When are overcomplete topic models identifiable? uniqueness of tensor tucker decompositions with structured sparsity": ["generic identifiability", "overcomplete representations", "tensor decomposition", "topic models"], "Absent data generating classifier for imbalanced class sizes": ["imbalanced data", "kernel fisher discriminant analysis", "two-class classification"], "Decision boundary for discrete Bayesian network classifiers": ["bayesian networks", "decision boundary", "lagrange basis", "polynomial threshold function", "supervised classification"], "A view of margin losses as regularizers of probability estimates": ["binding functions", "boosting", "classification", "generalization", "link functions", "loss functions", "margin losses", "probability elicitation", "regularization", "shrinkage"], "Online tensor methods for learning latent variable models": ["large datasets", "mixed membership stochastic blockmodel", "parallel implementation", "stochastic gradient descent", "tensor method", "topic modeling"], "Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior": ["bayesian", "convergence rate", "gaussian process", "nonparametric regression", "random design", "rate-optimal"], "CEKA: a tool for mining the wisdom of crowds": ["crowdsourcing", "inference", "learning from crowds", "multiple noisy labeling", "noise handling", "repeated labeling simulation"], "Linear dimensionality reduction: survey, insights, and generalizations": ["dimensionality reduction", "eigenvector problems", "matrix manifolds"], "The Randomized Causation Coefficient": ["causality", "cause-effect inference", "kernel mean embeddings", "random features"], "Optimality of Poisson processes intensity learning with Gaussian processes": ["adaptation to smoothness", "bayesian intensity learning", "gaussian process prior", "inhomogeneous poisson process", "optimal rates"], "Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013": ["feature generation", "paper-author identification"], "Comparing hard and overlapping clusterings": ["clustering evaluation", "fuzzy", "overlapping", "probabilistic"], "Completing any low-rank matrix, provably": ["coherence", "leverage score", "matrix completion", "nuclear norm", "weighted nuclear norm"], "Eigenwords: spectral word embeddings": ["cca", "nlp", "spectral learning", "word embeddings"], "Discrete reproducing kernel Hilbert spaces: sampling and distribution of Dirac-masses": ["discrete green's functions", "gaussian reproducing kernel hilbert spaces", "graph laplacians", "resistance metric", "sampling in discrete systems"], "A direct estimation of high dimensional stationary vector autoregressions": ["double asymptotic framework", "linear program", "multivariate time series", "transition matrix", "vector autoregressive model"], "Global convergence of online limited memory BFGS": ["large-scale optimization", "quasi-newton methods", "stochastic optimization"], "On semi-supervised linear regression in covariate shift problems": ["joint optimization", "semi-supervised regression", "usefulness of unlabeled data"], "Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery": ["causality", "experimental data", "large-scale experimental design", "local causal pathway discovery", "observational data", "randomized experiments"], "Plug-and-play dual-tree algorithm runtime analysis": ["adaptive runtime analysis", "cover tree", "dual-tree algorithms", "expansion constant", "kernel density estimation", "nearest neighbor search", "range search"], "Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates": ["computation complexity", "divide and conquer", "kernel ridge regression"], "Learning theory of randomized Kaczmarz algorithm": ["almost sure convergence", "learning theory", "online learning", "relaxed randomized kaczmarz algorithm", "space of homogeneous linear functions"], "Matrix completion and low-rank SVD via fast alternating least squares": ["alternating least squares", "matrix completion", "nuclear norm", "svd"], "On the inductive bias of dropout": ["dropout", "feature noising", "inductive bias", "learning theory", "regularization"], "Agnostic learning of disjunctions on symmetric distributions": ["agnostic learning", "conjunction", "decision tree", "disjunction", "dnf", "polynomial approximation", "regression", "symmetric distribution"], "SnFFT: a Julia toolkit for Fourier analysis of functions over permutations": ["fast fourier transform", "fourier analysis", "julia", "permutations"], "The sample complexity of learning linear predictors with the squared loss": ["distribution-free learning", "linear predictors", "sample complexity", "squared loss"], "Minimax analysis of active learning": ["active learning", "adaptive sampling", "margin condition", "minimax analysis", "sample complexity", "selective sampling", "sequential design", "statistical learning theory", "tsybakov noise"], "Convergence rates for persistence diagram estimation in topological data analysis": ["convergence rates", "persistent homology", "topological data analysis"], "Supervised learning via Euler's Elastica models": ["euler's elastica", "euler-lagrange pde", "function approximation", "geometric regularization", "supervised learning", "total variation", "universal consistency"], "Learning to identify concise regular expressions that describe email campaigns": ["applications of machine learning", "email campaigns", "learning with structured output spaces", "regular expressions", "supervised learning"], "Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards": ["finite-time regret", "large deviation principle", "stochastic bandit"], "Condition for perfect dimensionality recovery by variational Bayesian PCA": ["automatic relevance determination", "matrix factorization", "perfect dimensionality recovery", "principal component analysis", "variational bayesian learning"], "Graphical models via univariate exponential family distributions": ["graphical models", "model selection", "sparse estimation"], "Marginalizing stacked linear denoising autoencoders": ["denoising autoencoders", "domain adaption", "fast representation learning", "noise marginalization"], "PAC optimal MDP planning with application to invasive species management": ["good-turing estimate", "invasive species management", "markov decision processes", "mdp planning", "reinforcement learning"], "Partykit: a modular toolkit for recursive partytioning in R": ["classification trees", "r", "recursive partitioning", "regression trees", "statistical learning"]}, {"Xi Chen": "Tippie College of Business, University of Iowa, Iowa City, Iowa", "Qihang Lin": "Microsoft Research, Redmond, Washington", "Qi Yan": "Computer Science and Engineering, Arizona State University, Tempe, AZ", "Jieping Ye": "School of Statistics, University of Minnesota, Minneapolis, MN", "Michael Thon": "Jacobs University Bremen, Bremen, Germany", "Gianmarco De Francisci Morales": "Yahoo Labs, Barcelona, Spain", "Alexander Rakhlin": "Department of Computer Science, Cornell University, Ithaca, NY", "Karthik Sridharan": "Department of Statistics, University of Michigan, Ann Arbor, MI", "Qiang Qiu": "Department of Electrical and Computer Engineering, Department of Computer Science, Department of Biomedical Engineering, Duke University, Durham, NC", "Feng Jiang": "School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China", "Shengping Zhang": "School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China", "Shen Wu": "School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China", "Yang Gao": "School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China", "Vassilis Pitsikalis": "National Technical University of Athens, School of Electrical and Computer Engineering, Zografou Campus, Athens, Greece", "Athanasios Katsamanis": "National Technical University of Athens, School of Electrical and Computer Engineering, Zografou Campus, Athens, Greece", "Stavros Theodorakis": "National Technical University of Athens, School of Electrical and Computer Engineering, Zografou Campus, Athens, Greece", "Ji Liu": "Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI", "Stephen J. Wright": "Department of Computer Science, Stanford University, Stanford, CA", "Christopher R\u00e9": "Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI", "Victor Bittorf": "Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI", "\u00c0lvaro Barbero": "Department of Mathematical Informatics, The University of Tokyo, Tokyo, Japan", "Akiko Takeda": "Department of Computer Science and Knowledge-Engineering, Institute Autonomous, University of Madrid, Madrid, Spain", "Quoc Tran-Dinh": "LIONS, EPFL, Lausanne, Switzerland", "Anastasios Kyrillidis": "LIONS, EPFL, Lausanne, Switzerland", "Sumanta Basu": "Department of Biostatistics, University of Washington, Seattle, WA", "Ali Shojaie": "Department of Statistics, University of Michigan, Ann Arbor, MI", "Nir Ailon": "Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA", "Yudong Chen": "Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX", "Alberto Cano": "Department of Computer Science and Numerical Analysis Rabanales Campus, University of C\u00f3rdoba, C\u00f3rdoba, Spain", "Jos\u00e9 Mar\u00eda Luna": "Department of Computer Science and Numerical Analysis Rabanales Campus, University of C\u00f3rdoba, C\u00f3rdoba, Spain", "Amelia Zafra": "Department of Computer Science and Numerical Analysis Rabanales Campus, University of C\u00f3rdoba, C\u00f3rdoba, Spain", "Andr\u00e9 F. T. Martins": "Instituto de Telecomunica\u00e7\u00f5es, and Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal", "M\u00e1rio A. T. Figueiredo": "Instituto de Telecomunica\u00e7\u00f5es, and Instituto Superior T\u00e9cnico, Universidade de Lisboa, Lisboa, Portugal", "Pedro M. Q. Aguiar": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA", "Noah A. Smith": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA", "Felix Weninger": "Machine Learning & Signal Processing, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany", "Johannes Bergmann": "Machine Learning & Signal Processing, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany", "Xingguo Li": "Department of Computer Science, Johns Hopkins University, Baltimore, MD", "Tuo Zhao": "Department of Mathematics, Hong Kong Baptist University, Hong Kong, China", "Xiaoming Yuan": "Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ", "Po-Ling Loh": "Departments of EECS and Statistics, University of California, Berkeley, CA", "Pratik Jawanpuria": "Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Mumbai, India", "Jagarlapudi Saketha Nath": "Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Mumbai, India", "Guido Mont\u00fafar": "Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany and Department of Mathematics and Computer Science, Leipzig University, Leipzig, Germany and Santa Fe Institute, Santa Fe, NM", "Cleomar Pereira Da Silva": "Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil", "Douglas Mota Dias": "Department of Systems Engineering, State University of Rio de Janeiro, Rio de Janeiro, Brazil", "Cristiana Bentes": "Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil", "Marco Aur\u00e9lio Cavalcanti Pacheco": "Toulouse Institute of Computer Science Research, University of Toulouse, Toulouse Cedex 9, France", "Yair Wiener": "Computer Science Department, Technion-Israel Institute of Technology, Haifa, Israel", "Andrey Bernstein": "Department of Electrical Engineering, Technion\u2014Israel Institute of Technology, Haifa, Israel", "Pascal Germain": "D\u00e9partement d'informatique et de g\u00e9nie logiciel, Universit\u00e9 Laval, Qu\u00e9bec, Canada", "Alexandre Lacasse": "D\u00e9partement d'informatique et de g\u00e9nie logiciel, Universit\u00e9 Laval, Qu\u00e9bec, Canada", "Fran\u00e7ois Laviolette": "D\u00e9partement d'informatique et de g\u00e9nie logiciel, Universit\u00e9 Laval, Qu\u00e9bec, Canada", "Mario Marchand": "D\u00e9partement d'informatique et de g\u00e9nie logiciel, Universit\u00e9 Laval, Qu\u00e9bec, Canada", "Ping Ma": "International Computer Science Institute and Department of Statistics, University of California at Berkeley, Berkeley, CA", "Michael W. Mahoney": "Department of Statistics, University of California at Berkeley, Berkeley, CA", "Lester Mackey": "Computer Science Department, University of California, Los Angeles, Los Angeles, CA", "Ameet Talwalkar": "Department of Electrical Engineering and Computer Science and Department of Statistics, University of California, Berkeley, Berkeley, CA", "Piotr Pokarowski": "Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland and Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland", "Yunlong Feng": "Department of Electrical Engineering, ESAT-STADIUS, KU Leuven, Leuven, Belgium", "Xiaolin Huang": "Shanghai Key Laboratory for Contemporary Applied Mathematics, School of Mathematical Sciences, Fudan University, Shanghai, P.R. China", "Lei Shi": "Department of Electrical Engineering, ESAT-STADIUS, KU Leuven, Leuven, Belgium", "Yuning Yang": "Department of Electrical Engineering, ESAT-STADIUS, KU Leuven, Leuven, Belgium", "Wonyul Lee": "Department of Statistics and Operations Research, Department of Genetics, Department of Biostatistics, Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC", "Jie Wang": "Department of Computer Science and Engineering, Arizona State University, Tempe, AZ", "Peter Wonka": "Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI", "Tammo Krueger": "Technische Universit\u00e4t Berlin, Machine Learning Group, Berlin, Germany", "Danny Panknin": "Technische Universit\u00e4t Berlin, Machine Learning Group, Berlin, Germany", "Jean Honorio": "Department of Computer Science, Stony Brook University, Stony Brook, NY", "Siamak Ravanbakhsh": "Department of Computing Science, University of Alberta, Edmonton, AB, CA", "Sivan Sabato": "David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada", "Shai Shalev-Shwartz": "Toyota Technological Institute at Chicago, Chicago, IL", "Nathan Srebro": "Department of Computer Science, Columbia University, New York, NY", "Daniel Hsu": "Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA", "John Fearnley": "University of Liverpool, United Kingdom", "Martin Gairing": "University of Oxford, United Kingdom", "Paul W. Goldberg": "University of Liverpool, United Kingdom", "Peter Sunehag": "Research School of Computer Science, The Australian National University, ACT, Canberra, Australia", "Franz J. Kir\u00e1ly": "Aalto Science Institute and Department of Information and Computer Science, Aalto University, Espoo, Finland", "Louis Theran": "Toyota Technological Institute at Chicago, Chicago, Illinois", "Javier Garc\u00eda": "Universidad Carlos III de Madrid, Leganes, Madrid, Spain", "Edward Moroshko": "Department of Electrical Engineering, The Technion - Israel Institute of Technology, Haifa, Israel", "Nina Vaits": "Department of Electrical Engineering, The Technion - Israel Institute of Technology, Haifa, Israel", "Daniel Berend": "Department of Computer Science, Ben-Gurion University, Beer Sheva, Israel", "Xingye Qiao": "Department of Statistics, Purdue University, West Lafayette, IN", "Alborz Geramifard": "Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA", "Christoph Dann": "Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA", "Robert H. Klein": "Amazon.com, Seattle, WA", "William Dabney": "Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA", "Han Liu": "Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA", "Lie Wang": "Department of Computer Science, Johns Hopkins University, Baltimore, MD", "Pablo G. Moreno": "Gregorio Mara\u00f1\u00f3n Health Research Institute, Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Legan\u00e9s, Madrid, Spain", "Antonio Art\u00e9s-Rodr\u00edguez": "Department of Statistics, Oxford, UK", "Bruno Scherrer": "Adobe Research & INRIA Lille, San Jose, CA", "Mohammad Ghavamzadeh": "INRIA Lille-Nord Europe, Team SequeL, Villeneuve d'Ascq, France", "Victor Gabillon": "INRIA Nancy-Grand Est, Team Maia, Vand\u0153uvre-ls-Nancy, France", "Boris Lesner": "CentraleSup\u00e9lec, IMS-MaLIS Research Group & UMI, (GeorgiaTech-CNRS), Metz, France", "Alex Gammerman": "Computer Learning Research Centre, Department of Computer Science, University of London", "Vladimir Vapnik": "Applied Communication Sciences, Basking Ridge, NJ", "Adith Swaminathan": "Department of Computer Science, Cornell University, Ithaca, NY", "Vladimir Koltchinskii": "School of Mathematics, Georgia Institute of Technology, Atlanta, GA", "Tim Van Erven": "Centrum voor Wiskunde en Informatica and MI, Universiteit Leiden, Amsterdam, The Netherlands", "Peter D. Gr\u00fcnwald": "Centrum voor Wiskunde en Informatica, Amsterdam, The Netherlands", "Nishant A. Mehta": "Australian National University and NICTA, Canberra, ACT, Australia", "Mark D. Reid": "Australian National University and NICTA, Canberra, ACT, Australia", "L\u00e1szl\u00f3 Gy\u00f6rfi": "Department of Mathematics, University of Stuttgart, Stuttgart, Germany", "Pierre C. Bellec": "ENSAE, Malakoff, France", "Louigi Addario-Berry": "Department of Statistics and Operations Research, University of North, Carolina Chapel Hill, NC", "Shankar Bhamidi": "Microsoft Research, Redmond, WA", "S\u00e9bastien Bubeck": "School of Computer Science, McGill University, Montreal, Canada", "Luc Devroye": "ICREA and Pompeu Fabra University, Department of Economics and Business, Barcelona, Spain", "G\u00e1bor Lugosi": "IMPA, Rio de Janeiro, RJ, Brazil", "Dominik Janzing": "Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany", "Philipp Thomann": "Institute for Stochastics and Applications, University of Stuttgart, Germany", "Ingo Steinwart": "Institute for Stochastics and Applications, University of Stuttgart, Germany", "Mark Herbster": "Department of Computer Science, University College London, London, UK", "Stephen Pasteris": "Department of Computer Science, University College London, London, UK", "Michiel Hermans": "Instituto de F\u00edsica Interdisciplinar y Sistemas Complejos, IFISC, Palma de Mallorca, Spain", "Miguel C. Soriano": "ELIS departement, Ghent University, Ghent, Belgium", "Joni Dambre": "INTEC departement, Ghent University, Ghent, Belgium", "Peter Bienstman": "Instituto de F\u00edsica Interdisciplinar y Sistemas Complejos, Palma de Mallorca, Spain", "Jian Zhang": "School of Mathematics, Statistics and Actuarial Science, University of Kent, Kent, UK", "Sofia Triantafillou": "Institute of Computer Science, Foundation for Research and Technology, Hellas, FORTH, Heraklion, Crete, Greece and Department of Computer Science, University of Crete", "Alexandra Carpentier": "Google DeepMind, London, UK", "Bryon Aragam": "Department of Statistics, University of California, Los Angeles, Los Angeles, CA", "Narayana Santhanam": "EECS Dept, University of California, Berkeley, Berkeley, CA", "Kazuho Watanabe": "Helsinki Institute for Information Technology, Department of Computer Science, University of Helsinki, Finland", "Amit Daniely": "Dept. of Computer Science, Ben-Gurion University of Negev, Beer Sheva, Israel", "Shai Ben-David": "School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel", "Nihat Ay": "Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany", "Gianluca Bontempi": "Machine Learning Group, Computer Science Department, Interuniversity Institute of Bioinformatics in Brussels, Universit\u00e9 Libre de Bruxelles, Brussels, Belgium", "Daniel Lowd": "Department of Computer and Information Science, University of Oregon, Eugene, OR", "Ines Maru\u0161ic": "Department of Computer Science, University of Oxford, Oxford, UK", "Emily B. Fox": "Department of Statistical Science, Duke University, Durham, NC", "Yangbo He": "LMAM, School of Mathematical Sciences, LMEQF, and Center for Statistical Science, Peking University, Beijing, China", "Jinzhu Jia": "Departments of Statistics and EECS, University of California at Berkeley, Berkeley, CA", "Marion Neumann": "Fraunhofer IAIS, Augustin, Germany", "Shan Huang": "Sproutling, San Francisco, CA", "Wen Wu Wang": "Qilu Securities Institute for Financial Studies & School of Mathematics, Shandong University, Jinan, China", "Animashree Anandkumar": "Department of Computer Science, Columbia University, New York, NY", "Majid Janzamin": "Department of Computer Science, Department of Statistics, University of Washington, Seattle, WA", "Arash Pourhabib": "Department of Statistics, Texas A&M University, College Station, TX", "Bani K. Mallick": "Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX", "Gherardo Varando": "Departamento de Inteligencia Artificial, Universidad Polit\u00e9cnica de Madrid, Madrid, Spain", "Concha Bielza": "Departamento de Inteligencia Artificial, Universidad Polit\u00e9cnica de Madrid, Madrid, Spain", "Hamed Masnadi-Shirazi": "Statistical Visual Computing Laboratory, University of California, San Diego, La Jolla, CA", "Furong Huang": "Electrical Engineering and Computer Science Dept., University of California, Irvine, Irvine", "U. N. Niranjan": "Electrical Engineering and Computer Science Dept., University of California, Irvine, Irvine", "Mohammad Umar Hakeem": "Electrical Engineering and Computer Science Dept., University of California, Irvine, Irvine", "Debdeep Pati": "Department of Statistics, Texas A&M University, College Station, TX", "Anirban Bhattacharya": "Department of Statistics, Purdue University, West Lafayette, IN", "Jing Zhang": "Department of Computer Science, University of Central Arkansas, Conway, AR", "Victor S. Sheng": "Department of Computer Science, University of Central Arkansas, Conway, AR", "Bryce A. Nicholson": "School of Computer Science and Information Engineering, HFUT, Hefei, China and Department of Computer Science, University of Vermont, Burlington, VT", "John P. Cunningham": "Department of Engineering, University of Cambridge, Cambridge, UK", "David Lopez-Paz": "Max-Planck-Institute for Intelligent Systems, T\u00fcbingen, Germany", "Krikamol Muandet": "Department of EECS, University of California Berkeley, Berkeley, CA", "Alisa Kirichenko": "Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Amsterdam, The Netherlands", "Chun-Liang Li": "National Taiwan University, Taipei, Taiwan", "Yu-Chuan Su": "National Taiwan University, Taipei, Taiwan", "Ting-Wei Lin": "National Taiwan University, Taipei, Taiwan", "Cheng-Hao Tsai": "National Taiwan University, Taipei, Taiwan", "Wei-Cheng Chang": "National Taiwan University, Taipei, Taiwan", "Kuan-Hao Huang": "National Taiwan University, Taipei, Taiwan", "Tzu-Ming Kuo": "National Taiwan University, Taipei, Taiwan", "Shan-Wei Lin": "National Taiwan University, Taipei, Taiwan", "Young-San Lin": "National Taiwan University, Taipei, Taiwan", "Yu-Chen Lu": "National Taiwan University, Taipei, Taiwan", "Chun-Pai Yang": "National Taiwan University, Taipei, Taiwan", "Cheng-Xia Chang": "National Taiwan University, Taipei, Taiwan", "Wei-Sheng Chin": "National Taiwan University, Taipei, Taiwan", "Yu-Chin Juan": "National Taiwan University, Taipei, Taiwan", "Hsiao-Yu Tung": "National Taiwan University, Taipei, Taiwan", "Jui-Pin Wang": "National Taiwan University, Taipei, Taiwan", "Cheng-Kuang Wei": "National Taiwan University, Taipei, Taiwan", "Felix Wu": "National Taiwan University, Taipei, Taiwan", "Tu-Chun Yin": "National Taiwan University, Taipei, Taiwan", "Tong Yu": "National Taiwan University, Taipei, Taiwan", "Yong Zhuang": "National Taiwan University, Taipei, Taiwan", "Shou-De Lin": "National Taiwan University, Taipei, Taiwan", "Hsuan-Tien Lin": "National Taiwan University, Taipei, Taiwan", "Danilo Horta": "Instituto de Ci\u00eancias Matem\u00e1t\u00edcas e de Computa\u00e7\u00e3o, Universidade de S\u00e3o Paulo, S\u00e3o Carlos-SP, Brazil", "Srinadh Bhojanapalli": "Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX", "Sujay Sanghavi": "Department of Mathematics and ICES, The University of Texas at Austin, Austin, TX", "Paramveer S. Dhillon": "Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA", "Dean P. Foster": "Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA", "Palle Jorgensen": "Department of Mathematics, Informatics, and Cybersecurity, Trine University, Angola, IN", "Fang Han": "Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ", "Huanran Lu": "Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ", "Aryan Mokhtari": "Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA", "Kenneth Joseph Ryan": "Department of Statistics, West Virginia University, Morgantown, WV", "Alexander Statnikov": "Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY", "Sisi Ma": "Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY", "Mikael Henaff": "Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY", "Nikita Lytkin": "Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY", "Efstratios Efstathiadis": "Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY", "Eric R. Peskin": "Institute for Health Informatics, University of Minnesota, Minneapolis, MN", "Ryan R. Curtin": "Yahoo Labs, Sunnyvale, CA", "Dongryeol Lee": "Institute for Computational Engineering and Sciences, University of Texas, Austin, Austin, TX", "William B. March": "Skytree, Inc., Atlanta, GA", "Yuchen Zhang": "Departments of Statistics and Electrical Engineering, Stanford University, Stanford, CA", "John Duchi": "Departments of Statistics and Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA", "Junhong Lin": "Department of Mathematics, City University of Hong Kong, Kowloon, Hong Kong, China", "Trevor Hastie": "Department of Statistics, Columbia University, New York, NY", "Rahul Mazumder": "Institute for Computational and Mathematical Engineering, Stanford University, CA", "Jason D. Lee": "Databricks, Berkeley, CA", "David P. Helmbold": "Microsoft, Sunnyvale, CA", "Vitaly Feldman": "Department of Computer Science, The University of Texas at Austin, Austin, TX", "Gregory Plumb": "Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI", "Deepti Pachauri": "Department of Computer Sciences, University of Chicago, Chicago, IL and Department of Statistics", "Risi Kondor": "Department of Biostatistics & Med. Info., University of Wisconsin-Madison, Madison, WI", "Fr\u00e9d\u00e9ric Chazal": "Universit\u00e9 de Bourgogne, Institut de Mathematiques de Bourgogne, UMR, CNRS, Dijon, France", "Marc Glisse": "Universit\u00e8 de Bourgogne, Dijon, France", "Catherine Labru\u00e8re": "LSTA, Universit\u00e9 Pierre et Marie Curie Paris 6, Paris, France", "Tong Lin": "Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China", "Hanlin Xue": "Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China", "Ling Wang": "Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China", "Bo Huang": "Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China", "Paul Prasse": "SoundCloud Ltd., Berlin, Germany", "Niels Landwehr": "University of Potsdam, Department of Computer Science, Potsdam, Germany", "Junya Honda": "Department of Mathematical Informatics, The University of Tokyo, Tokyo, Japan", "Shinichi Nakajima": "Toyota Technological Institute at Chicago, Chicago, IL", "Ryota Tomioka": "Department of Complexity Science and Engineering, The University of Tokyo, Tokyo, Japan", "Masashi Sugiyama": "Google Inc., Mountain View, CA", "Eunho Yang": "Department of Computer Science, University of Texas, Austin, Austin, TX", "Pradeep Ravikumar": "Department of Statistics, Rice University, Houston, TX", "Genevera I. 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