Journal of Machine Learning Research, Volume 3
Volume 3, July 2002
- Nader H. Bshouty, Nadav Eiron:
Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries. 49-57 - 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
Volume 3, September 2002
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
Volume 3, November 2002
- 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 - 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
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
- 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 - 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 - 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
Volume 3, January 2003
Volume 3, Febuary 2003
- 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
- Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter:
Distributional Word Clusters vs. Words for Text Categorization. 1183-1208 - 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 - Simon Perkins, Kevin Lacker, James Theiler:
Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space. 1333-1356 - 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 - Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping:
Use of the Zero-Norm with Linear Models and Kernel Methods. 1439-1461