Journal of Machine Learning Research

The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online.
Published
Stability of Density-Based Clustering; Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry Wasserman; 13(Apr):905--948, 2012.
Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features; Gil Tahan, Lior Rokach, Yuval Shahar; 13(Apr):949--979, 2012.
Sampling Methods for the Nyström Method; Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar; 13(Apr):981--1006, 2012.
Positive Semidefinite Metric Learning Using Boosting-like Algorithms; Chunhua Shen, Junae Kim, Lei Wang, Anton van den Hengel; 13(Apr):1007--1036, 2012.
Consistent Model Selection Criteria on High Dimensions; Yongdai Kim, Sunghoon Kwon, Hosik Choi; 13(Apr):1037--1057, 2012.
The huge Package for High-dimensional Undirected Graph Estimation in R; Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman; 13(Apr):1059--1062, 2012.
Analysis of a Random Forests Model; Gérard Biau; 13(Apr):1063--1095, 2012.
Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies; Ioannis Tsamardinos, Sofia Triantafillou, Vincenzo Lagani; 13(Apr):1097--1157, 2012.
Hope and Fear for Discriminative Training of Statistical Translation Models; David Chiang; 13(Apr):1159--1187, 2012.
A Multi-Stage Framework for Dantzig Selector and LASSO; Ji Liu, Peter Wonka, Jieping Ye; 13(Apr):1189--1219, 2012.
A Geometric Approach to Sample Compression; Benjamin I.P. Rubinstein, J. Hyam Rubinstein; 13(Apr):1221--1261, 2012.
Published
A Primal-Dual Convergence Analysis of Boosting; Matus Telgarsky; 13(Mar):561--606, 2012.
MULTIBOOST: A Multi-purpose Boosting Package; Djalel Benbouzid, Róbert Busa-Fekete, Norman Casagrande, François-David Collin, Balázs Kégl; 13(Mar):549--553, 2012.
ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel; Stephen R. Piccolo, Lewis J. Frey; 13(Mar):555--559, 2012.
Metric and Kernel Learning Using a Linear Transformation; Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon; 13(Mar):519--547, 2012.
Non-Sparse Multiple Kernel Fisher Discriminant Analysis; Fei Yan, Josef Kittler, Krystian Mikolajczyk, Atif Tahir; 13(Mar):607--642, 2012.
Learning Algorithms for the Classification Restricted Boltzmann Machine; Hugo Larochelle, Michael Mandel, Razvan Pascanu, Yoshua Bengio; 13(Mar):643--669, 2012.
Structured Sparsity and Generalization; Andreas Maurer, Massimiliano Pontil; 13(Mar):671--690, 2012.
A Case Study on Meta-Generalising: A Gaussian Processes Approach; Grigorios Skolidis, Guido Sanguinetti; 13(Mar):691--721, 2012.
A Kernel Two-Sample Test; Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander Smola; 13(Mar):723--773, 2012.
GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression; Chiwoo Park, Jianhua Z. Huang, Yu Ding; 13(Mar):775--779, 2012.
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso; Rahul Mazumder, Trevor Hastie; 13(Mar):781--794, 2012.
Algorithms for Learning Kernels Based on Centered Alignment; Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh; 13(Mar):795--828, 2012.
Causal Bounds and Observable Constraints for Non-deterministic Models; Roland R. Ramsahai; 13(Mar):829--848, 2012.
NIMFA : A Python Library for Nonnegative Matrix Factorization; Marinka Žitnik, Blaž Zupan; 13(Mar):849--853, 2012.
Algebraic Geometric Comparison of Probability Distributions; Franz J. Király, Paul von Bünau, Frank C. Meinecke, Duncan A.J. Blythe, Klaus-Robert Müller; 13(Mar):855--903, 2012.
Published
Active Learning via Perfect Selective Classification; Ran El-Yaniv, Yair Wiener; 13(Feb):255--279, 2012.
Multi Kernel Learning with Online-Batch Optimization; Francesco Orabona, Luo Jie, Barbara Caputo; 13(Feb):227--253, 2012.
Random Search for Hyper-Parameter Optimization; James Bergstra, Yoshua Bengio; 13(Feb):281--305, 2012.
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics; Michael U. Gutmann, Aapo Hyvärinen; 13(Feb):307--361, 2012.
Bounding the Probability of Error for High Precision Optical Character Recognition; Gary B. Huang, Andrew Kae, Carl Doersch, Erik Learned-Miller; 13(Feb):363--387, 2012.
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming; Garvesh Raskutti, Martin J. Wainwright, Bin Yu; 13(Feb):389--427, 2012.
Online Learning in the Embedded Manifold of Low-rank Matrices; Uri Shalit, Daphna Weinshall, Gal Chechik; 13(Feb):429--458, 2012.
Multi-Assignment Clustering for Boolean Data; Mario Frank, Andreas P. Streich, David Basin, Joachim M. Buhmann; 13(Feb):459--489, 2012.
Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks; Vikas C. Raykar, Shipeng Yu; 13(Feb):491--518, 2012.
Published
Distance Metric Learning with Eigenvalue Optimization; Yiming Ying, Peng Li; 13(Jan):1--26, 2012.
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection; Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luján; 13(Jan):27--66, 2012.
Plug-in Approach to Active Learning; Stanislav Minsker; 13(Jan):67--90, 2012.
Refinement of Operator-valued Reproducing Kernels; Haizhang Zhang, Yuesheng Xu, Qinghui Zhang; 13(Jan):91--136, 2012.
An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity; Nir Ailon; 13(Jan):137--164, 2012.
Optimal Distributed Online Prediction Using Mini-Batches; Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao; 13(Jan):165--202, 2012.
Active Clustering of Biological Sequences; Konstantin Voevodski, Maria-Florina Balcan, Heiko Röglin, Shang-Hua Teng, Yu Xia; 13(Jan):203--225, 2012.
Published
A Simpler Approach to Matrix Completion; Benjamin Recht; 12(Dec):3413--3430, 2011.
Convergence of Distributed Asynchronous Learning Vector Quantization Algorithms; Benoît Patra; 12(Dec):3431--3466, 2011.
Published
In All Likelihood, Deep Belief Is Not Enough; Lucas Theis, Sebastian Gerwinn, Fabian Sinz, Matthias Bethge; 12(Nov):3071--3096, 2011.
Efficient and Effective Visual Codebook Generation Using Additive Kernels; Jianxin Wu, Wei-Chian Tan, James M. Rehg; 12(Nov):3097--3118, 2011.
Unsupervised Supervised Learning II: Margin-Based Classification Without Labels; Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon; 12(Nov):3119--3145, 2011.
Adaptive Exact Inference in Graphical Models; Özgür Sümer, Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu; 12(Nov):3147--3186, 2011.
Group Lasso Estimation of High-dimensional Covariance Matrices; Jérémie Bigot, Rolando J. Biscay, Jean-Michel Loubes, Lillian Muñiz-Alvarez; 12(Nov):3187--3225, 2011.
Robust Gaussian Process Regression with a Student-t Likelihood; Pasi Jylänki, Jarno Vanhatalo, Aki Vehtari; 12(Nov):3227--3257, 2011.
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