JMLR Volume 14

• Global Analytic Solution of Fully-observed Variational Bayesian Matrix Factorization

  Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan, Ryota Tomioka (1):1−37, 2013 PDF BibTeX

• Ranking Forests

  Stéphan Clémençon, Marine Depecker, Nicolas Vayatis (2):39−73, 2013 PDF BibTeX

• Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood

  Jaakko Riihimäki, Pasi Jylänki, Aki Vehtari (3):75−109, 2013 PDF BibTeX

• Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models

  Aapo Hyvärinen, Stephen M. Smith (4):111−152, 2013 PDF BibTeX

• Universal Consistency of Localized Versions of Regularized Kernel Methods

  Robert Hable (5):153−186, 2013 PDF BibTeX

• Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem

  Antoine Salomon, Jean-Yves Audibert, Issam El Alaoui (6):187−207, 2013 PDF BibTeX

• MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures With Low Probability of False Positives During Use

  Daniel Kyu Hwa Kohlsdorf, Thad E. Starner (7):209−242, 2013 PDF BibTeX

• Sparse Single-Index Model

  Pierre Alquier, Gérard Biau (8):243−280, 2013 PDF BibTeX

• Using Symmetry and Evolutionary Search to Minimize Sorting Networks

  Vinod K. Valsalam, Risto Miikkulainen (9):303−331, 2013 PDF BibTeX

• A Framework for Evaluating Approximation Methods for Gaussian Process Regression

  Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray (10):303−331, 2013 PDF BibTeX

• On the Learnability of Shuffle Ideals

  Dana Angluin, James Aspnes, Sarah Eisenstat, Aryeh Kontorovich (11):1513−1531, 2013 PDF BibTeX

• Fast Generalized Subset Scan for Anomalous Pattern Detection

  Edward McFowl, III, Skyler Speakman, Daniel B. Neill (12):1533−1561, 2013 PDF BibTeX

• Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections

  Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi (13):399−436, 2013 PDF BibTeX

• A Theory of Multiclass Boosting

  Indraneel Mukherjee, Robert E. Schapire (14):437−497, 2013 PDF BibTeX

• Algorithms for Discovery of Multiple Markov Boundaries

  Alexander Statnikov, Nikita I. Lytkin, Jan Lemeire, Constantin F. Aliferis (15):499−566, 2013 PDF BibTeX

• Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

  Shai Shalev-Shwartz, Tong Zhang (16):567−599, 2013 PDF BibTeX

• Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality

  Sébastien Bubeck, Damien Ernst, Aurélien Garivier (17):601−623, 2013 PDF BibTeX

• A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics

  Hervé Frezza-Buet, Matthieu Geist (18):625−628, 2013 codePDF BibTeX

• CODA: High Dimensional Copula Discriminant Analysis

  Fang Han, Tuo Zhao, Han Liu (19):629−671, 2013 PDF BibTeX

• Bayesian Nonparametric Hidden Semi-Markov Models

  Matthew J. Johnson, Alan S. Willsky (20):673−701, 2013 PDF BibTeX

• Differential Privacy for Functions and Functional Data

  Rob Hall, Alessandro Rinaldo, Larry Wasserman (21):703−727, 2013 PDF BibTeX

• Sparsity Regret Bounds for Individual Sequences in Online Linear Regression

  Sébastien Gerchinovitz (22):729−769, 2013 PDF BibTeX

• Semi-Supervised Learning Using Greedy Max-Cut

  Jun Wang, Tony Jebara, Shih-Fu Chang (23):771−800, 2013 PDF BibTeX

• MLPACK: A Scalable C++ Machine Learning Library

  Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray (24):801−805, 2013 codePDF BibTeX

• Greedy Sparsity-Constrained Optimization

  Sohail Bahmani, Bhiksha Raj, Petros T. Boufounos (25):807−841, 2013 PDF BibTeX

• Quasi-Newton Method: A New Direction

  Philipp Hennig, Martin Kiefel (26):843−865, 2013 PDF BibTeX

• A Widely Applicable Bayesian Information Criterion

  Sumio Watanabe (27):867−897, 2013 PDF BibTeX

• Truncated Power Method for Sparse Eigenvalue Problems

  Xiao-Tong Yuan, Tong Zhang (28):899−925, 2013 PDF BibTeX

• Query Induction with Schema-Guided Pruning Strategies

  Joachim Niehren, Jérôme Champavère, Aurélien Lemay, Rémi Gilleron (29):927−964, 2013 PDF BibTeX

• Bayesian Canonical Correlation Analysis

  Arto Klami, Seppo Virtanen, Samuel Kaski (30):965−1003, 2013 PDF BibTeX

• Bayesian Canonical Correlation Analysis

  Chong Wang, David M. Blei (31):965−1003, 2013 PDF BibTeX

• Beyond Fano's Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications

  Ming-Jie Zhao, Narayanan Edakunni, Adam Pocock, Gavin Brown (32):1033−1090, 2013 PDF BibTeX

• Sparse Activity and Sparse Connectivity in Supervised Learning

  Markus Thom, Günther Palm (33):1091−1143, 2013 PDF BibTeX

• Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing

  Lisha Chen, Andreas Buja (34):1145−1173, 2013 PDF BibTeX

• GPstuff: Bayesian Modeling with Gaussian Processes

  Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, Aki Vehtari (35):1175−1179, 2013 codePDF BibTeX

• Performance Bounds for λ Policy Iteration and Application to the Game of Tetris

  Bruno Scherrer (36):1181−1227, 2013 PDF BibTeX

• Manifold Regularization and Semi-supervised Learning: Some Theoretical Analyses

  Partha Niyogi (37):1229−1250, 2013 PDF BibTeX

• Random Spanning Trees and the Prediction of Weighted Graphs

  Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella (38):1251−1284, 2013 PDF BibTeX

• Regularization-Free Principal Curve Estimation

  Samuel Gerber, Ross Whitaker (39):1285−1302, 2013 PDF BibTeX

• Stochastic Variational Inference

  Matthew D. Hoffman, David M. Blei, Chong Wang, John Paisley (40):1303−1347, 2013 PDF BibTeX

• Multicategory Large-Margin Unified Machines

  Chong Zhang, Yufeng Liu (41):1349−1386, 2013 PDF BibTeX

• Finding Optimal Bayesian Networks Using Precedence Constraints

  Pekka Parviainen, Mikko Koivisto (42):1387−1415, 2013 PDF BibTeX

• JKernelMachines: A Simple Framework for Kernel Machines

  David Picard, Nicolas Thome, Matthieu Cord (43):1417−1421, 2013 codePDF BibTeX

• Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators

  Pierre Neuvial (44):1423−1459, 2013 PDF BibTeX

• Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems

  Takafumi Kanamori, Akiko Takeda, Taiji Suzuki (45):1461−1504, 2013 PDF BibTeX

• A Risk Comparison of Ordinary Least Squares vs Ridge Regression

  Paramveer S. Dhillon, Dean P. Foster, Sham M. Kakade, Lyle H. Ungar (46):1505−1511, 2013 PDF BibTeX

• Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling

  Shusen Wang, Zhihua Zhang (47):2729−2769, 2013 PDF BibTeX

• Training Energy-Based Models for Time-Series Imputation

  Philémon Brakel, Dirk Stroobandt, Benjamin Schrauwen (48):2771−2797, 2013 PDF BibTeX

• Sub-Local Constraint-Based Learning of Bayesian Networks Using A Joint Dependence Criterion

  Rami Mahdi, Jason Mezey (49):1563−1603, 2013 PDF BibTeX

• Dimension Independent Similarity Computation

  Reza Bosagh Zadeh, Ashish Goel (50):1605−1626, 2013 PDF BibTeX

• Dynamic Affine-Invariant Shape-Appearance Handshape Features and Classification in Sign Language Videos

  Anastasios Roussos, Stavros Theodorakis, Vassilis Pitsikalis, Petros Maragos (51):1627−1663, 2013 PDF BibTeX

• Nonparametric Sparsity and Regularization

  Lorenzo Rosasco, Silvia Villa, Sofia Mosci, Matteo Santoro, Aless, ro Verri (52):1665−1714, 2013 PDF BibTeX

• Similarity-based Clustering by Left-Stochastic Matrix Factorization

  Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel (53):1715−1746, 2013 PDF BibTeX

• On the Convergence of Maximum Variance Unfolding

  Ery Arias-Castro, Bruno Pelletier (54):1747−1770, 2013 PDF BibTeX

• Variable Selection in High-Dimension with Random Designs and Orthogonal Matching Pursuit

  Antony Joseph (55):1771−1800, 2013 PDF BibTeX

• Random Walk Kernels and Learning Curves for Gaussian Process Regression on Random Graphs

  Matthew J. Urry, Peter Sollich (56):1801−1835, 2013 PDF BibTeX

• Distributions of Angles in Random Packing on Spheres

  Tony Cai, Jianqing Fan, Tiefeng Jiang (57):1837−1864, 2013 PDF BibTeX

• Cluster Analysis: Unsupervised Learning via Supervised Learning with a Non-convex Penalty

  Wei Pan, Xiaotong Shen, Binghui Liu (58):1865−1889, 2013 PDF BibTeX

• Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation

  Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont (59):1891−1945, 2013 PDF BibTeX

• Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting

  Nayyar A. Zaidi, Jesús Cerquides, Mark J. Carman, Geoffrey I. Webb (60):1947−1988, 2013 PDF BibTeX

• Machine Learning with Operational Costs

  Theja Tulab, hula, Cynthia Rudin (61):1989−2028, 2013 PDF BibTeX

• Approximating the Permanent with Fractional Belief Propagation

  Michael Chertkov, Adam B. Yedidia (62):2029−2066, 2013 PDF BibTeX

• Construction of Approximation Spaces for Reinforcement Learning

  Wendelin Böhmer, Steffen Grünewälder, Yun Shen, Marek Musial, Klaus Obermayer (63):2067−2118, 2013 PDF BibTeX

• Distribution-Dependent Sample Complexity of Large Margin Learning

  Sivan Sabato, Nathan Srebro, Naftali Tishby (64):2119−2149, 2013 PDF BibTeX

• Convex and Scalable Weakly Labeled SVMs

  Yu-Feng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou (65):2151−2188, 2013 PDF BibTeX

• Language-Motivated Approaches to Action Recognition

  Manavender R. Malgireddy, Ifeoma Nwogu, Venu Govindaraju (66):2189−2212, 2013 PDF BibTeX

• Segregating Event Streams and Noise with a Markov Renewal Process Model

  Dan Stowell, Mark D. Plumbley (67):2213−2238, 2013 PDF BibTeX

• Gaussian Kullback-Leibler Approximate Inference

  Edward Challis, David Barber (68):2239−2286, 2013 PDF BibTeX

• Message-Passing Algorithms for Quadratic Minimization

  Nicholas Ruozzi, Sekhar Tatikonda (69):2287−2314, 2013 PDF BibTeX

• The Rate of Convergence of AdaBoost

  Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire (70):2315−2347, 2013 PDF BibTeX

• Orange: Data Mining Toolbox in Python

  Janez Demšar, Tomaž Curk, Aleš Erjavec, Črt Gorup, Tomaž Hočevar, Mitar Milutinovič, Martin Možina, Matija Polajnar, Marko Toplak, Anže Starič, Miha Štajdohar, Lan Umek, Lan Žagar, Jure Žbontar, Marinka Žitnik, Blaž Zupan (71):2349−2353, 2013 codePDF BibTeX

• Tapkee: An Efficient Dimension Reduction Library

  Sergey Lisitsyn, Christian Widmer, Fernando J. Iglesias Garcia (72):2355−2359, 2013 codePDF BibTeX

• On the Mutual Nearest Neighbors Estimate in Regression

  Arnaud Guyader, Nick Hengartner (73):2361−2376, 2013 PDF BibTeX

• Distance Preserving Embeddings for General n-Dimensional Manifolds

  Nakul Verma (74):2415−2448, 2013 PDF BibTeX

• Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows

  Julien Mairal, Bin Yu (75):2449−2485, 2013 PDF BibTeX

• Greedy Feature Selection for Subspace Clustering

  Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk (76):2487−2517, 2013 PDF BibTeX

• Learning Bilinear Model for Matching Queries and Documents

  Wei Wu, Zhengdong Lu, Hang Li (77):2519−2548, 2013 PDF BibTeX

• One-shot Learning Gesture Recognition from RGB-D Data Using Bag of Features

  Jun Wan, Qiuqi Ruan, Wei Li, Shuang Deng (78):2549−2582, 2013 PDF BibTeX

• Efficient Active Learning of Halfspaces: An Aggressive Approach

  Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz (79):2583−2615, 2013 PDF BibTeX

• Keep It Simple And Sparse: Real-Time Action Recognition

  Sean Ryan Fanello, Ilaria Gori, Giorgio Metta, Francesca Odone (80):2617−2640, 2013 PDF BibTeX

• Maximum Volume Clustering: A New Discriminative Clustering Approach

  Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama (81):2641−2687, 2013 PDF BibTeX

• Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory

  Aleks, r Y. Aravkin, James V. Burke, Gianluigi Pillonetto (82):2689−2728, 2013 PDF BibTeX

• Optimally Fuzzy Temporal Memory

  Karthik H. Shankar, Marc W. Howard (83):3785−3812, 2013 PDF BibTeX

• BudgetedSVM: A Toolbox for Scalable SVM Approximations

  Nemanja Djuric, Liang Lan, Slobodan Vucetic, Zhuang Wang (84):3813−3817, 2013 codePDF BibTeX

• Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees

  Nima Noorshams, Martin J. Wainwright (85):2799−2835, 2013 PDF BibTeX

• A Binary-Classification-Based Metric between Time-Series Distributions and Its Use in Statistical and Learning Problems

  Daniil Ryabko, Jérémie Mary (86):2837−2856, 2013 PDF BibTeX

• Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models

  Manfred Opper, Ulrich Paquet, Ole Winther (87):2857−2898, 2013 PDF BibTeX

• The CAM Software for Nonnegative Blind Source Separation in R-Java

  Niya Wang, Fan Meng, Li Chen, Subha Madhavan, Robert Clarke, Eric P. Hoffman, Jianhua Xuan, Yue Wang (88):2899−2903, 2013 codePDF BibTeX

• A Near-Optimal Algorithm for Differentially-Private Principal Components

  Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha (89):2905−2943, 2013 PDF BibTeX

• Parallel Vector Field Embedding

  Binbin Lin, Xiaofei He, Chiyuan Zhang, Ming Ji (90):2945−2977, 2013 PDF BibTeX

• Multi-Stage Multi-Task Feature Learning

  Pinghua Gong, Jieping Ye, Changshui Zhang (91):2979−3010, 2013 PDF BibTeX

• A Plug-in Approach to Neyman-Pearson Classification

  Xin Tong (92):3011−3040, 2013 PDF BibTeX

• Experiment Selection for Causal Discovery

  Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer (93):3041−3071, 2013 PDF BibTeX

• Stationary-Sparse Causality Network Learning

  Yuejia He, Yiyuan She, Dapeng Wu (94):3073−3104, 2013 PDF BibTeX

• Algorithms and Hardness Results for Parallel Large Margin Learning

  Philip M. Long, Rocco A. Servedio (95):3105−3128, 2013 PDF BibTeX

• Large-scale SVD and Manifold Learning

  Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri, Henry Rowley (96):3129−3152, 2013 PDF BibTeX

• QuantMiner for Mining Quantitative Association Rules

  Ansaf Salleb-Aouissi, Christel Vrain, Cyril Nortet, Xiangrong Kong, Vivek Rathod, Daniel Cassard (97):3153−3157, 2013 codePDF BibTeX

• Divvy: Fast and Intuitive Exploratory Data Analysis

  Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten (98):3159−3163, 2013 codewebpagePDF BibTeX

• Using Symmetry and Evolutionary Search to Minimize Sorting Networks

  Qiang Liu, Alexander Ihler (99):303−331, 2013 PDF BibTeX

• GURLS: A Least Squares Library for Supervised Learning

  Andrea Tacchetti, Pavan K. Mallapragada, Matteo Santoro, Lorenzo Rosasco (100):3201−3205, 2013 codePDF BibTeX

• Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising

  Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, Ed Snelson (101):3207−3260, 2013 PDF BibTeX

• Multivariate Convex Regression with Adaptive Partitioning

  Lauren A. Hannah, David B. Dunson (102):3261−3294, 2013 PDF BibTeX

• Fast MCMC Sampling for Markov Jump Processes and Extensions

  Vinayak Rao, Yee Whye Teh (103):3295−3320, 2013 PDF BibTeX

• Communication-Efficient Algorithms for Statistical Optimization

  Yuchen Zhang, John C. Duchi, Martin J. Wainwright (104):3321−3363, 2013 PDF BibTeX

• PC Algorithm for Nonparanormal Graphical Models

  Naftali Harris, Mathias Drton (105):3365−3383, 2013 PDF BibTeX

• Sparse Matrix Inversion with Scaled Lasso

  Tingni Sun, Cun-Hui Zhang (106):3385−3418, 2013 PDF BibTeX

• Consistent Selection of Tuning Parameters via Variable Selection Stability

  Wei Sun, Junhui Wang, Yixin Fang (107):3419−3440, 2013 PDF BibTeX

• Learning Theory Analysis for Association Rules and Sequential Event Prediction

  Cynthia Rudin, Benjamin Letham, David Madigan (108):3441−3492, 2013 PDF BibTeX

• Comment on "Robustness and Regularization of Support Vector Machines" by H. Xu et al. (Journal of Machine Learning Research, vol. 10, pp. 1485-1510, 2009)

  Yahya Forghani, Hadi Sadoghi (109):3493−3494, 2013 PDF BibTeX

• Lovasz theta function, SVMs and Finding Dense Subgraphs

  Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi (110):3495−3536, 2013 PDF BibTeX

• Learning Trees from Strings: A Strong Learning Algorithm for some Context-Free Grammars

  Alexander Clark (111):3537−3559, 2013 PDF BibTeX

• Classifying With Confidence From Incomplete Information

  Nathan Parrish, Hyrum S. Anderson, Maya R. Gupta, Dun Yu Hsiao (112):3561−3589, 2013 PDF BibTeX

• Classifier Selection using the Predicate Depth

  Ran Gilad-Bachrach, Christopher J.C. Burges (113):3591−3618, 2013 PDF BibTeX

• A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion

  Tony Cai, Wen-Xin Zhou (114):3619−3647, 2013 PDF BibTeX

• Efficient Program Synthesis Using Constraint Satisfaction in Inductive Logic Programming

  John Ahlgren, Shiu Yin Yuen (115):3649−3681, 2013 PDF BibTeX

• How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis

  Alberto N. Escalante-B., Laurenz Wiskott (116):3683−3719, 2013 PDF BibTeX

• Joint Harmonic Functions and Their Supervised Connections

  Mark Vere Culp, Kenneth Joseph Ryan (117):3721−3752, 2013 PDF BibTeX

• Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels

  Kenji Fukumizu, Le Song, Arthur Gretton (118):3753−3783, 2013 PDF BibTeX