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JMLR Volume 16

Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling
Xi Chen, Qihang Lin, Dengyong Zhou; (1):1−46, 2015.
[abs][pdf][bib]

Simultaneous Pursuit of Sparseness and Rank Structures for Matrix Decomposition
Qi Yan, Jieping Ye, Xiaotong Shen; (2):47−75, 2015.
[abs][pdf][bib]

Statistical Topological Data Analysis using Persistence Landscapes
Peter Bubenik; (3):77−102, 2015.
[abs][pdf][bib]

Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework
Michael Thon, Herbert Jaeger; (4):103−147, 2015.
[abs][pdf][bib]

SAMOA: Scalable Advanced Massive Online Analysis
Gianmarco De Francisci Morales, Albert Bifet; (5):149−153, 2015.
[abs][pdf][bib]      [code]

Online Learning via Sequential Complexities
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari; (6):155−186, 2015.
[abs][pdf][bib]

Learning Transformations for Clustering and Classification
Qiang Qiu, Guillermo Sapiro; (7):187−225, 2015.
[abs][pdf][bib]

Multi-layered Gesture Recognition with Kinect
Feng Jiang, Shengping Zhang, Shen Wu, Yang Gao, Debin Zhao; (8):227−254, 2015.
[abs][pdf][bib]

Multimodal Gesture Recognition via Multiple Hypotheses Rescoring
Vassilis Pitsikalis, Athanasios Katsamanis, Stavros Theodorakis, Petros Maragos; (9):255−284, 2015.
[abs][pdf][bib]

An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar; (10):285−322, 2015.
[abs][pdf][bib]

Geometric Intuition and Algorithms for Ev--SVM
Álvaro Barbero, Akiko Takeda, Jorge López; (11):323−369, 2015.
[abs][pdf][bib]

Composite Self-Concordant Minimization
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher; (12):371−416, 2015.
[abs][pdf][bib]

Network Granger Causality with Inherent Grouping Structure
Sumanta Basu, Ali Shojaie, George Michailidis; (13):417−453, 2015.
[abs][pdf][bib]

Iterative and Active Graph Clustering Using Trace Norm Minimization Without Cluster Size Constraints
Nir Ailon, Yudong Chen, Huan Xu; (14):455−490, 2015.
[abs][pdf][bib]

A Classification Module for Genetic Programming Algorithms in JCLEC
Alberto Cano, José María Luna, Amelia Zafra, Sebastián Ventura; (15):491−494, 2015.
[abs][pdf][bib]      [code]

AD3: Alternating Directions Dual Decomposition for MAP Inference in Graphical Models
André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing; (16):495−545, 2015.
[abs][pdf][bib]

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit
Felix Weninger; (17):547−551, 2015.
[abs][pdf][bib]      [code]

The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu; (18):553−557, 2015.
[abs][pdf][bib]      [code] [webpage]

Regularized M-estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima
Po-Ling Loh, Martin J. Wainwright; (19):559−616, 2015.
[abs][pdf][bib]

Generalized Hierarchical Kernel Learning
Pratik Jawanpuria, Jagarlapudi Saketha Nath, Ganesh Ramakrishnan; (20):617−652, 2015.
[abs][pdf][bib]

Discrete Restricted Boltzmann Machines
Guido Montúfar, Jason Morton; (21):653−672, 2015.
[abs][pdf][bib]

Evolving GPU Machine Code
Cleomar Pereira da Silva, Douglas Mota Dias, Cristiana Bentes, Marco Aur\'{e}lio Cavalcanti Pacheco, Le, ro Fontoura Cupertino; (22):673−712, 2015.
[abs][pdf][bib]

A Compression Technique for Analyzing Disagreement-Based Active Learning
Yair Wiener, Steve Hanneke, Ran El-Yaniv; (23):713−745, 2015.
[abs][pdf][bib]

Response-Based Approachability with Applications to Generalized No-Regret Problems
Andrey Bernstein, Nahum Shimkin; (24):747−773, 2015.
[abs][pdf][bib]

Strong Consistency of the Prototype Based Clustering in Probabilistic Space
Vladimir Nikulin; (25):775−785, 2015.
[abs][pdf][bib]

Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm
Pascal Germain, Alex, re Lacasse, Francois Laviolette, Mario March, , Jean-Francis Roy; (26):787−860, 2015.
[abs][pdf][bib]

A Statistical Perspective on Algorithmic Leveraging
Ping Ma, Michael W. Mahoney, Bin Yu; (27):861−911, 2015.
[abs][pdf][bib]

Distributed Matrix Completion and Robust Factorization
Lester Mackey, Ameet Talwalkar, Michael I. Jordan; (28):913−960, 2015.
[abs][pdf][bib]

Combined l1 and Greedy l0 Penalized Least Squares for Linear Model Selection
Piotr Pokarowski, Jan Mielniczuk; (29):961−992, 2015.
[abs][pdf][bib]

Learning with the Maximum Correntropy Criterion Induced Losses for Regression
Yunlong Feng, Xiaolin Huang, Lei Shi, Yuning Yang, Johan A.K. Suykens; (30):993−1034, 2015.
[abs][pdf][bib]

Joint Estimation of Multiple Precision Matrices with Common Structures
Wonyul Lee, Yufeng Liu; (31):1035−1062, 2015.
[abs][pdf][bib]

Lasso Screening Rules via Dual Polytope Projection
Jie Wang, Peter Wonka, Jieping Ye; (32):1063−1101, 2015.
[abs][pdf][bib]

Fast Cross-Validation via Sequential Testing
Tammo Krueger, Danny Panknin, Mikio Braun; (33):1103−1155, 2015.
[abs][pdf][bib]

Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data
Jean Honorio, Luis Ortiz; (34):1157−1210, 2015.
[abs][pdf][bib]

Local Identification of Overcomplete Dictionaries
Karin Schnass; (35):1211−1242, 2015.
[abs][pdf][bib]      [erratum]

Encog: Library of Interchangeable Machine Learning Models for Java and C#
Jeff Heaton; (36):1243−1247, 2015.
[abs][pdf][bib]      [code] [webpage]

Perturbed Message Passing for Constraint Satisfaction Problems
Siamak Ravanbakhsh, Russell Greiner; (37):1249−1274, 2015.
[abs][pdf][bib]

Learning Sparse Low-Threshold Linear Classifiers
Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel Hsu, Tong Zhang; (38):1275−1304, 2015.
[abs][pdf][bib]

Learning Equilibria of Games via Payoff Queries
John Fearnley, Martin Gairing, Paul W. Goldberg, Rahul Savani; (39):1305−1344, 2015.
[abs][pdf][bib]

Rationality, Optimism and Guarantees in General Reinforcement Learning
Peter Sunehag, Marcus Hutter; (40):1345−1390, 2015.
[abs][pdf][bib]

The Algebraic Combinatorial Approach for Low-Rank Matrix Completion
Franz J.Király, Louis Theran, Ryota Tomioka; (41):1391−1436, 2015.
[abs][pdf][bib]

A Comprehensive Survey on Safe Reinforcement Learning
Javier García, Fern, o Fernández; (42):1437−1480, 2015.
[abs][pdf][bib]

Second-Order Non-Stationary Online Learning for Regression
Edward Moroshko, Nina Vaits, Koby Crammer; (43):1481−1517, 2015.
[abs][pdf][bib]

A Finite Sample Analysis of the Naive Bayes Classifier
Daniel Berend, Aryeh Kontorovich; (44):1519−1545, 2015.
[abs][pdf][bib]

Flexible High-Dimensional Classification Machines and Their Asymptotic Properties
Xingye Qiao, Lingsong Zhang; (45):1547−1572, 2015.
[abs][pdf][bib]

RLPy: A Value-Function-Based Reinforcement Learning Framework for Education and Research
Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How; (46):1573−1578, 2015.
[abs][pdf][bib]      [code]

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery
Han Liu, Lie Wang, Tuo Zhao; (47):1579−1606, 2015.
[abs][pdf][bib]

Bayesian Nonparametric Crowdsourcing
Pablo G. Moreno, Antonio Artes-Rodriguez, Yee Whye Teh, Fern, o Perez-Cruz; (48):1607−1627, 2015.
[abs][pdf][bib]

Approximate Modified Policy Iteration and its Application to the Game of Tetris
Bruno Scherrer, Mohammad Ghavamzadeh, Victor Gabillon, Boris Lesner, Matthieu Geist; (49):1629−1676, 2015.
[abs][pdf][bib]

Preface to this Special Issue
Alex Gammerman, Vladimir Vovk; (50):1677−1681, 2015.
[abs][pdf][bib]

V-Matrix Method of Solving Statistical Inference Problems
Vladimir Vapnik, Rauf Izmailov; (51):1683−1730, 2015.
[abs][pdf][bib]

Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization
Adith Swaminathan, Thorsten Joachims; (52):1731−1755, 2015.
[abs][pdf][bib]

Optimal Estimation of Low Rank Density Matrices
Vladimir Koltchinskii, Dong Xia; (53):1757−1792, 2015.
[abs][pdf][bib]

Fast Rates in Statistical and Online Learning
Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson; (54):1793−1861, 2015.
[abs][pdf][bib]

On the Asymptotic Normality of an Estimate of a Regression Functional
László Györfi, Harro Walk; (55):1863−1877, 2015.
[abs][pdf][bib]

Sharp Oracle Bounds for Monotone and Convex Regression Through Aggregation
Pierre C. Bellec, Alex, re B. Tsybakov; (56):1879−1892, 2015.
[abs][pdf][bib]

Exceptional Rotations of Random Graphs: A VC Theory
Louigi Addario-Berry, Shankar Bhamidi, Sébastien Bubeck, Luc Devroye, Gábor Lugosi, Roberto Imbuzeiro Oliveira; (57):1893−1922, 2015.
[abs][pdf][bib]

Semi-Supervised Interpolation in an Anticausal Learning Scenario
Dominik Janzing, Bernhard Schölkopf; (58):1923−1948, 2015.
[abs][pdf][bib]

Towards an Axiomatic Approach to Hierarchical Clustering of Measures
Philipp Thomann, Ingo Steinwart, Nico Schmid; (59):1949−2002, 2015.
[abs][pdf][bib]

Predicting a Switching Sequence of Graph Labelings
Mark Herbster, Stephen Pasteris, Massimiliano Pontil; (60):2003−2022, 2015.
[abs][pdf][bib]

Learning Using Privileged Information: Similarity Control and Knowledge Transfer
Vladimir Vapnik, Rauf Izmailov; (61):2023−2049, 2015.
[abs][pdf][bib]

Alexey Chervonenkis's Bibliography: Introductory Comments
Alex Gammerman, Vladimir Vovk; (62):2051−2066, 2015.
[abs][pdf][bib]

Alexey Chervonenkis's Bibliography
Alex Gammerman, Vladimir Vovk; (63):2067−2080, 2015.
[abs][pdf][bib]

Photonic Delay Systems as Machine Learning Implementations
Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer; (64):2081−2097, 2015.
[abs][pdf][bib]

On Linearly Constrained Minimum Variance Beamforming
Jian Zhang, Chao Liu; (65):2099−2145, 2015.
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Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets
Sofia Triantafillou, Ioannis Tsamardinos; (66):2147−2205, 2015.
[abs][pdf][bib]

Existence and Uniqueness of Proper Scoring Rules
Evgeni Y. Ovcharov; (67):2207−2230, 2015.
[abs][pdf][bib]

Adaptive Strategy for Stratified Monte Carlo Sampling
Alex, ra Carpentier, Remi Munos, András Antos; (68):2231−2271, 2015.
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Concave Penalized Estimation of Sparse Gaussian Bayesian Networks
Bryon Aragam, Qing Zhou; (69):2273−2328, 2015.
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Agnostic Insurability of Model Classes
Narayana Santhanam, Venkat Anantharam; (70):2329−2355, 2015.
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Achievability of Asymptotic Minimax Regret by Horizon-Dependent and Horizon-Independent Strategies
Kazuho Watanabe, Teemu Roos; (71):2357−2375, 2015.
[abs][pdf][bib]

Multiclass Learnability and the ERM Principle
Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz; (72):2377−2404, 2015.
[abs][pdf][bib]

Geometry and Expressive Power of Conditional Restricted Boltzmann Machines
Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi; (73):2405−2436, 2015.
[abs][pdf][bib]

From Dependency to Causality: A Machine Learning Approach
Gianluca Bontempi, Maxime Flauder; (74):2437−2457, 2015.
[abs][pdf][bib]

The Libra Toolkit for Probabilistic Models
Daniel Lowd, Amirmohammad Rooshenas; (75):2459−2463, 2015.
[abs][pdf][bib]      [code]

Complexity of Equivalence and Learning for Multiplicity Tree Automata
Ines Marusic, James Worrell; (76):2465−2500, 2015.
[abs][pdf][bib]

Bayesian Nonparametric Covariance Regression
Emily B. Fox, David B. Dunson; (77):2501−2542, 2015.
[abs][pdf][bib]

A General Framework for Fast Stagewise Algorithms
Ryan J. Tibshirani; (78):2543−2588, 2015.
[abs][pdf][bib]

Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs
Yangbo He, Jinzhu Jia, Bin Yu; (79):2589−2609, 2015.
[abs][pdf][bib]

pyGPs -- A Python Library for Gaussian Process Regression and Classification
Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting; (80):2611−2616, 2015.
[abs][pdf][bib]      [code]

Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression
WenWu Wang, Lu Lin; (81):2617−2641, 2015.
[abs][pdf][bib]

When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity
Animashree An, kumar, Daniel Hsu, Majid Janzamin, Sham Kakade; (82):2643−2694, 2015.
[abs][pdf][bib]

Absent Data Generating Classifier for Imbalanced Class Sizes
Arash Pourhabib, Bani K. Mallick, Yu Ding; (83):2695−2724, 2015.
[abs][pdf][bib]

Decision Boundary for Discrete Bayesian Network Classifiers
Gherardo Var, o, Concha Bielza, Pedro Larranaga; (84):2725−2749, 2015.
[abs][pdf][bib]

A View of Margin Losses as Regularizers of Probability Estimates
Hamed Masnadi-Shirazi, Nuno Vasconcelos; (85):2751−2795, 2015.
[abs][pdf][bib]

Online Tensor Methods for Learning Latent Variable Models
Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree An, kumar; (86):2797−2835, 2015.
[abs][pdf][bib]

Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior
Debdeep Pati, Anirban Bhattacharya, Guang Cheng; (87):2837−2851, 2015.
[abs][pdf][bib]

CEKA: A Tool for Mining the Wisdom of Crowds
Jing Zhang, Victor S. Sheng, Bryce A. Nicholson, Xindong Wu; (88):2853−2858, 2015.
[abs][pdf][bib]      [code]

Linear Dimensionality Reduction: Survey, Insights, and Generalizations
John P. Cunningham, Zoubin Ghahramani; (89):2859−2900, 2015.
[abs][pdf][bib]

The Randomized Causation Coefficient
David Lopez-Paz, Krikamol Mu, et, Benjamin Recht; (90):2901−2907, 2015.
[abs][pdf][bib]

Optimality of Poisson Processes Intensity Learning with Gaussian Processes
Alisa Kirichenko, Harry van Zanten; (91):2909−2919, 2015.
[abs][pdf][bib]

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; (92):2921−2947, 2015.
[abs][pdf][bib]

Comparing Hard and Overlapping Clusterings
Danilo Horta, Ricardo J.G.B. Campello; (93):2949−2997, 2015.
[abs][pdf][bib]

Completing Any Low-rank Matrix, Provably
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward; (94):2999−3034, 2015.
[abs][pdf][bib]

Eigenwords: Spectral Word Embeddings
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar; (95):3035−3078, 2015.
[abs][pdf][bib]

Discrete Reproducing Kernel Hilbert Spaces: Sampling and Distribution of Dirac-masses
Palle Jorgensen, Feng Tian; (96):3079−3114, 2015.
[abs][pdf][bib]

A Direct Estimation of High Dimensional Stationary Vector Autoregressions
Fang Han, Huanran Lu, Han Liu; (97):3115−3150, 2015.
[abs][pdf][bib]

Global Convergence of Online Limited Memory BFGS
Aryan Mokhtari, Alej, ro Ribeiro; (98):3151−3181, 2015.
[abs][pdf][bib]

On Semi-Supervised Linear Regression in Covariate Shift Problems
Kenneth Joseph Ryan, Mark Vere Culp; (99):3183−3217, 2015.
[abs][pdf][bib]

Ultra-Scalable and Efficient Methods for Hybrid Observational and Experimental Local Causal Pathway Discovery
Alex, er Statnikov, Sisi Ma, Mikael Henaff, Nikita Lytkin, Efstratios Efstathiadis, Eric R. Peskin, Constantin F. Aliferis; (100):3219−3267, 2015.
[abs][pdf][bib]

Plug-and-Play Dual-Tree Algorithm Runtime Analysis
Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram; (101):3269−3297, 2015.
[abs][pdf][bib]

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
Yuchen Zhang, John Duchi, Martin Wainwright; (102):3299−3340, 2015.
[abs][pdf][bib]

Learning Theory of Randomized Kaczmarz Algorithm
Junhong Lin, Ding-Xuan Zhou; (103):3341−3365, 2015.
[abs][pdf][bib]

Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh; (104):3367−3402, 2015.
[abs][pdf][bib]

On the Inductive Bias of Dropout
David P. Helmbold, Philip M. Long; (105):3403−3454, 2015.
[abs][pdf][bib]

Agnostic Learning of Disjunctions on Symmetric Distributions
Vitaly Feldman, Pravesh Kothari; (106):3455−3467, 2015.
[abs][pdf][bib]

SnFFT: A Julia Toolkit for Fourier Analysis of Functions over Permutations
Gregory Plumb, Deepti Pachauri, Risi Kondor, Vikas Singh; (107):3469−3473, 2015.
[abs][pdf][bib]

The Sample Complexity of Learning Linear Predictors with the Squared Loss
Ohad Shamir; (108):3475−3486, 2015.
[abs][pdf][bib]

Minimax Analysis of Active Learning
Steve Hanneke, Liu Yang; (109):3487−3602, 2015.
[abs][pdf][bib]

Convergence Rates for Persistence Diagram Estimation in Topological Data Analysis
Frédéric Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel; (110):3603−3635, 2015.
[abs][pdf][bib]

Supervised Learning via Euler's Elastica Models
Tong Lin, Hanlin Xue, Ling Wang, Bo Huang, Hongbin Zha; (111):3637−3686, 2015.
[abs][pdf][bib]

Learning to Identify Concise Regular Expressions that Describe Email Campaigns
Paul Prasse, Christoph Sawade, Niels L, wehr, Tobias Scheffer; (112):3687−3720, 2015.
[abs][pdf][bib]

Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards
Junya Honda, Akimichi Takemura; (113):3721−3756, 2015.
[abs][pdf][bib]

Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan; (114):3757−3811, 2015.
[abs][pdf][bib]

Graphical Models via Univariate Exponential Family Distributions
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zh, ong Liu; (115):3813−3847, 2015.
[abs][pdf][bib]

Marginalizing Stacked Linear Denoising Autoencoders
Minmin Chen, Kilian Q. Weinberger, Zhixiang (Eddie) Xu, Fei Sha; (116):3849−3875, 2015.
[abs][pdf][bib]

PAC Optimal MDP Planning with Application to Invasive Species Management
Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, H. Jo Albers; (117):3877−3903, 2015.
[abs][pdf][bib]

partykit: A Modular Toolkit for Recursive Partytioning in R
Torsten Hothorn, Achim Zeileis; (118):3905−3909, 2015.
[abs][pdf][bib]      [code]

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