JMLR Volume 3

Kernel Independent Component Analysis (Kernel Machines Section)
Francis R. Bach, Michael I. Jordan; 3(Jul):1-48, 2002.
[abs] [pdf] [ps.gz] [ps]

Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries
Nader H. Bshouty, Nadav Eiron; 3(Jul):49-57, 2002.
[abs] [pdf] [ps.gz] [ps]

On the Convergence of Optimistic Policy Iteration
John N. Tsitsiklis; 3(Jul):59-72, 2002.
[abs] [pdf] [ps.gz] [ps]

Data-dependent margin-based generalization bounds for classification
András Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi; 3(Jul):73-98, 2002.
[abs] [pdf] [ps.gz] [ps]

Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski; 3(Aug):99-114, 2002.
[abs] [pdf] [ps.gz] [ps]

Learning Precise Timing with LSTM Recurrent Networks
Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber; 3(Aug):115-143, 2002.
[abs] [pdf] [ps.gz] [ps]

ε-MDPs: Learning in Varying Environments
István Szita, Bálint Takács, András Lörincz; 3(Aug):145-174, 2002.
[abs] [pdf] [ps.gz] [ps] [html]

Algorithmic Luckiness
Ralf Herbrich, Robert C. Williamson; 3(Sep):175-212, 2002.
[abs] [pdf] [ps.gz] [ps]
errata: [pdf] [ps.gz] [ps]

R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
Ronen I. Brafman, Moshe Tennenholtz; 3(Oct):213-231, 2002.
[abs] [pdf] [ps.gz] [ps]

PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification     (Kernel Machines Section)
Matthias Seeger; 3(Oct):233-269, 2002.
[abs] [pdf] [ps.gz] [ps]

On Online Learning of Decision Lists
Ziv Nevo, Ran El-Yaniv; 3(Oct):271-301, 2002.
[abs] [pdf] [ps.gz] [ps]

Minimal Kernel Classifiers     (Kernel Machines Section)
Glenn M. Fung, Olvi L. Mangasarian, Alexander J. Smola; 3(Nov):303-321, 2002.
[abs] [pdf] [ps.gz] [ps]

The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces     (Kernel Machines Section)
Masashi Sugiyama, Klaus-Robert Müller; 3(Nov):323-359, 2002.
[abs] [pdf] [ps.gz] [ps]

Introduction to the Special Issue on Computational Learning Theory
Philip M. Long; 3(Nov):361-362, 2002.
[abs] [pdf] [ps.gz] [ps]

Tracking a Small Set of Experts by Mixing Past Posteriors
Olivier Bousquet, Manfred K. Warmuth; 3(Nov):363-396, 2002.
[abs] [pdf] [ps.gz] [ps]

Using Confidence Bounds for Exploitation-Exploration Trade-offs
Peter Auer; 3(Nov):397-422, 2002.
[abs] [pdf] [ps.gz] [ps]

Efficient Algorithms for Universal Portfolios
Adam Kalai, Santosh Vempala; 3(Nov):423-440, 2002.
[abs] [pdf] [ps.gz] [ps]

Limitations of Learning Via Embeddings in Euclidean Half Spaces
Shai Ben-David, Nadav Eiron, Hans Ulrich Simon; 3(Nov):441-461, 2002.
[abs] [pdf] [ps.gz] [ps]

Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
Peter L. Bartlett, Shahar Mendelson; 3(Nov):463-482, 2002.
[abs] [pdf] [ps.gz] [ps]

On Boosting with Polynomially Bounded Distributions
Nader H. Bshouty, Dmitry Gavinsky; 3(Nov):483-506, 2002.
[abs] [pdf] [ps.gz] [ps]

Optimal Structure Identification With Greedy Search
David Maxwell Chickering; 3(Nov):507-554, 2002.
[abs] [pdf] [ps.gz] [ps]
erratum: [pdf] [ps.gz] [ps]

A Robust Minimax Approach to Classification
Gert R.G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan; 3(Dec):555-582, 2002.
[abs] [pdf] [ps.gz] [ps]

Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions
Alexander Strehl, Joydeep Ghosh; 3(Dec):583-617, 2002.
[abs] [pdf] [ps.gz] [ps]

Special Issue on the Eighteenth International Conference on Machine Learning (ICML2001)
Carla E. Brodley, Andrea P. Danyluk; 3(Dec):619-620, 2002.
[abs] [pdf] [ps.gz] [ps]

Efficient Algorithms for Decision Tree Cross-validation
Hendrik Blockeel, Jan Struyf; 3(Dec):621-650, 2002.
[abs] [pdf] [ps.gz] [ps]

Multiple-Instance Learning of Real-Valued Data
Daniel R. Dooly, Qi Zhang, Sally A. Goldman, Robert A. Amar; 3(Dec):651-678, 2002.
[abs] [pdf] [ps.gz] [ps]

Learning Probabilistic Models of Link Structure
Lisa Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar; 3(Dec):679-707, 2002.
[abs] [pdf] [ps.gz] [ps]

The Representational Power of Discrete Bayesian Networks
Charles X. Ling, Huajie Zhang; 3(Dec):709-721, 2002.
[abs] [pdf] [ps.gz] [ps]

The Set Covering Machine
Mario Marchand, John Shawe-Taylor; 3(Dec):723-746, 2002.
[abs] [pdf] [ps.gz] [ps]

Coupled Clustering: A Method for Detecting Structural Correspondence
Zvika Marx, Ido Dagan, Joachim M. Buhmann, Eli Shamir; 3(Dec):747-780, 2002.
[abs] [pdf] [ps.gz] [ps]

Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
Prasanth B. Nair, Arindam Choudhury, Andy J. Keane; 3(Dec):781-801, 2002.
[abs] [pdf] [ps.gz] [ps]

Lyapunov Design for Safe Reinforcement Learning
Theodore J. Perkins, Andrew G. Barto; 3(Dec):803-832, 2002.
[abs] [pdf] [ps.gz] [ps]

Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling
Tobias Scheffer, Stefan Wrobel; 3(Dec):833-862, 2002.
[abs] [pdf] [ps.gz] [ps]

Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem
Marc Sebban, Richard Nock, Stéphane Lallich; 3(Dec):863-885, 2002.
[abs] [pdf] [ps.gz] [ps]

Learning to Construct Fast Signal Processing Implementations
Bryan Singer, Manuela Veloso; 3(Dec):887-919, 2002.
[abs] [pdf] [ps.gz] [ps]

Policy Search using Paired Comparisons
Malcolm J. A. Strens, Andrew W. Moore; 3(Dec):921-950, 2002.
[abs] [pdf] [ps.gz] [ps]

Ultraconservative Online Algorithms for Multiclass Problems
Koby Crammer, Yoram Singer; 3(Jan):951-991, 2003.
[abs] [pdf] [ps.gz] [ps]

Latent Dirichlet Allocation
David M. Blei, Andrew Y. Ng, Michael I. Jordan; 3(Jan):993-1022, 2003.
[abs] [pdf] [ps.gz] [ps]

Introduction to the Special Issue on Machine Learning Methods for Text and Images
Jaz Kandola, Thomas Hofmann, Tomaso Poggio, John Shawe-Taylor; 3(Feb):1023-1024, 2003.
[abs] [pdf] [ps.gz] [ps]

A Family of Additive Online Algorithms for Category Ranking
Koby Crammer, Yoram Singer; 3(Feb):1025-1058, 2003.
[abs] [pdf] [ps.gz] [ps]

Word-Sequence Kernels
Nicola Cancedda, Eric Gaussier, Cyril Goutte, Jean-Michel Renders; 3(Feb):1059-1082, 2003.
[abs] [pdf] [ps.gz] [ps]

Kernel Methods for Relation Extraction
Dmitry Zelenko, Chinatsu Aone, Anthony Richardella; 3(Feb):1083-1106, 2003.
[abs] [pdf] [ps.gz] [ps]

Matching Words and Pictures
Kobus Barnard, Pinar Duygulu, David Forsyth, Nando de Freitas,David M. Blei, Michael I. Jordan; 3(Feb):1107-1135, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

A Neural Probabilistic Language Model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Jauvin; 3(Feb):1137-1155, 2003.
[abs] [pdf] [ps.gz] [ps]

An Introduction to Variable and Feature Selection     (Kernel Machines Section)
Isabelle Guyon, André Elisseeff; 3(Mar):1157-1182, 2003.
[abs] [pdf] [ps.gz] [ps]

Distributional Word Clusters vs. Words for Text Categorization     (Kernel Machines Section)
Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter; 3(Mar):1183-1208, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

Extensions to Metric-Based Model Selection
Yoshua Bengio, Nicolas Chapados; 3(Mar):1209-1227, 2003.
[abs] [pdf] [ps.gz] [ps]

Dimensionality Reduction via Sparse Support Vector Machines     (Kernel Machines Section)
Jinbo Bi, Kristin Bennett, Mark Embrechts, Curt Breneman, Minghu Song; 3(Mar):1229-1243, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

Benefitting from the Variables that Variable Selection Discards
Rich Caruana, Virginia R. de Sa; 3(Mar):1245-1264, 2003.
[abs] [pdf] [ps.gz] [ps]

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification     (Kernel Machines Section)
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar; 3(Mar):1265-1287, 2003.
[abs] [pdf] [ps.gz] [ps]

An Extensive Empirical Study of Feature Selection Metrics for Text Classification     (Kernel Machines Section)
George Forman; 3(Mar):1289-1305, 2003.
[abs] [pdf] [ps.gz] [ps] full paper with appendices: [pdf] [ps.gz] [ps]     [data]

Sufficient Dimensionality Reduction     (Kernel Machines Section)
Amir Globerson, Naftali Tishby; 3(Mar):1307-1331, 2003.
[abs] [pdf] [ps.gz] [ps]

Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space     (Kernel Machines Section)
Simon Perkins, Kevin Lacker, James Theiler; 3(Mar):1333-1356, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

Variable Selection Using SVM-based Criteria     (Kernel Machines Section)
Alain Rakotomamonjy; 3(Mar):1357-1370, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

Overfitting in Making Comparisons Between Variable Selection Methods
Juha Reunanen; 3(Mar):1371-1382, 2003.
[abs] [pdf] [ps.gz] [ps]

MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling
Isabelle Rivals, Léon Personnaz; 3(Mar):1383-1398, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

Ranking a Random Feature for Variable and Feature Selection
Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois, Yacine Oussar; 3(Mar):1399-1414, 2003.
[abs] [pdf] [ps.gz] [ps]

Feature Extraction by Non-Parametric Mutual Information Maximization     (Kernel Machines Section)
Kari Torkkola; 3(Mar):1415-1438, 2003.
[abs] [pdf] [ps.gz] [ps]     [demos]

Use of the Zero-Norm with Linear Models and Kernel Methods     (Kernel Machines Section)
Jason Weston, André Elisseeff, Bernhard Schölkopf, Mike Tipping; 3(Mar):1439-1461, 2003.
[abs] [pdf] [ps.gz] [ps]     [data]

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