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Journal of Machine Learning Research, Volume 3
Volume 3, July 2002
- Francis R. Bach, Michael I. Jordan:
Kernel Independent Component Analysis. 1-48 - Nader H. Bshouty, Nadav Eiron:
Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries. 49-57 - John N. Tsitsiklis:
On the Convergence of Optimistic Policy Iteration. 59-72 - András Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi:
Data-dependent margin-based generalization bounds for classification. 73-98
Volume 3, August 2002
- Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski:
Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components. 99-114 - Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber:
Learning Precise Timing with LSTM Recurrent Networks. 115-143 - Istvan Szita, Bálint Takács, András Lörincz:
MDPs: Learning in Varying Environments. 145-174
Volume 3, September 2002
- Ralf Herbrich, Robert C. Williamson:
Algorithmic Luckiness. 175-212
Volume 3, October 2002
- Ronen I. Brafman, Moshe Tennenholtz:
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning. 213-231 - Matthias W. Seeger:
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification. 233-269 - Ziv Nevo, Ran El-Yaniv:
On Online Learning of Decision Lists. 271-301
Volume 3, November 2002
- Glenn Fung, Olvi L. Mangasarian, Alexander J. Smola:
Minimal Kernel Classifiers. 303-321 - Masashi Sugiyama, Klaus-Robert Müller:
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces. 323-359
- Olivier Bousquet, Manfred K. Warmuth:
Tracking a Small Set of Experts by Mixing Past Posteriors. 363-396 - Peter Auer:
Using Confidence Bounds for Exploitation-Exploration Trade-offs. 397-422 - Adam Kalai, Santosh S. Vempala:
Efficient Algorithms for Universal Portfolios. 423-440 - Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
Limitations of Learning Via Embeddings in Euclidean Half Spaces. 441-461 - Peter L. Bartlett, Shahar Mendelson:
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. 463-482 - Nader H. Bshouty, Dmitry Gavinsky:
On Boosting with Polynomially Bounded Distributions. 483-506 - David Maxwell Chickering:
Optimal Structure Identification With Greedy Search. 507-554
Volume 3, December 2002
- Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan:
A Robust Minimax Approach to Classification. 555-582 - Alexander Strehl, Joydeep Ghosh:
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions. 583-617
- Hendrik Blockeel, Jan Struyf:
Efficient Algorithms for Decision Tree Cross-validation. 621-650 - Daniel R. Dooly, Qi Zhang, Sally A. Goldman, Robert A. Amar:
Multiple-Instance Learning of Real-Valued Data. 651-678 - Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar:
Learning Probabilistic Models of Link Structure. 679-707 - Charles X. Ling, Huajie Zhang:
The Representational Power of Discrete Bayesian Networks. 709-721 - Mario Marchand, John Shawe-Taylor:
The Set Covering Machine. 723-746 - Zvika Marx, Ido Dagan, Joachim M. Buhmann, Eli Shamir:
Coupled Clustering: A Method for Detecting Structural Correspondence. 747-780 - Prasanth B. Nair, Arindam Choudhury, Andy J. Keane:
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels. 781-801 - Theodore J. Perkins, Andrew G. Barto:
Lyapunov Design for Safe Reinforcement Learning. 803-832 - Tobias Scheffer, Stefan Wrobel:
Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling. 833-862 - Marc Sebban, Richard Nock, Stéphane Lallich:
Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. 863-885 - Bryan Singer, Manuela M. Veloso:
Learning to Construct Fast Signal Processing Implementations. 887-919 - Malcolm J. A. Strens, Andrew W. Moore:
Policy Search using Paired Comparisons. 921-950
Volume 3, January 2003
- Koby Crammer, Yoram Singer:
Ultraconservative Online Algorithms for Multiclass Problems. 951-991 - David M. Blei, Andrew Y. Ng, Michael I. Jordan:
Latent Dirichlet Allocation. 993-1022
Volume 3, Febuary 2003
- Koby Crammer, Yoram Singer:
A Family of Additive Online Algorithms for Category Ranking. 1025-1058 - Nicola Cancedda, Éric Gaussier, Cyril Goutte, Jean-Michel Renders:
Word-Sequence Kernels. 1059-1082 - Dmitry Zelenko, Chinatsu Aone, Anthony Richardella:
Kernel Methods for Relation Extraction. 1083-1106 - Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando de Freitas, David M. Blei, Michael I. Jordan:
Matching Words and Pictures. 1107-1135 - Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin:
A Neural Probabilistic Language Model. 1137-1155
Volume 3, March 2003
- Isabelle Guyon, André Elisseeff:
An Introduction to Variable and Feature Selection. 1157-1182 - Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter:
Distributional Word Clusters vs. Words for Text Categorization. 1183-1208 - Yoshua Bengio, Nicolas Chapados:
Extensions to Metric-Based Model Selection. 1209-1227 - Jinbo Bi, Kristin P. Bennett, Mark J. Embrechts, Curt M. Breneman, Minghu Song:
Dimensionality Reduction via Sparse Support Vector Machines. 1229-1243 - Rich Caruana, Virginia R. de Sa:
Benefitting from the Variables that Variable Selection Discards. 1245-1264 - Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar:
A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. 1265-1287 - George Forman:
An Extensive Empirical Study of Feature Selection Metrics for Text Classification. 1289-1305 - Amir Globerson, Naftali Tishby:
Sufficient Dimensionality Reduction. 1307-1331 - Simon Perkins, Kevin Lacker, James Theiler:
Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space. 1333-1356 - Alain Rakotomamonjy:
Variable Selection Using SVM-based Criteria. 1357-1370 - Juha Reunanen:
Overfitting in Making Comparisons Between Variable Selection Methods. 1371-1382 - Isabelle Rivals, Léon Personnaz:
MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling. 1383-1398 - Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois, Yacine Oussar:
Ranking a Random Feature for Variable and Feature Selection. 1399-1414 - Kari Torkkola:
Feature Extraction by Non-Parametric Mutual Information Maximization. 1415-1438 - Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping:
Use of the Zero-Norm with Linear Models and Kernel Methods. 1439-1461
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