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Publication search results
found 56 matches
- 2003
- Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando de Freitas, David M. Blei, Michael I. Jordan:
Matching Words and Pictures. J. Mach. Learn. Res. 3: 1107-1135 (2003) - Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter:
Distributional Word Clusters vs. Words for Text Categorization. J. Mach. Learn. Res. 3: 1183-1208 (2003) - Yoshua Bengio, Nicolas Chapados:
Extensions to Metric-Based Model Selection. J. Mach. Learn. Res. 3: 1209-1227 (2003) - Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin:
A Neural Probabilistic Language Model. J. Mach. Learn. Res. 3: 1137-1155 (2003) - Jinbo Bi, Kristin P. Bennett, Mark J. Embrechts, Curt M. Breneman, Minghu Song:
Dimensionality Reduction via Sparse Support Vector Machines. J. Mach. Learn. Res. 3: 1229-1243 (2003) - David M. Blei, Andrew Y. Ng, Michael I. Jordan:
Latent Dirichlet Allocation. J. Mach. Learn. Res. 3: 993-1022 (2003) - Nicola Cancedda, Éric Gaussier, Cyril Goutte, Jean-Michel Renders:
Word-Sequence Kernels. J. Mach. Learn. Res. 3: 1059-1082 (2003) - Rich Caruana, Virginia R. de Sa:
Benefitting from the Variables that Variable Selection Discards. J. Mach. Learn. Res. 3: 1245-1264 (2003) - Koby Crammer, Yoram Singer:
Ultraconservative Online Algorithms for Multiclass Problems. J. Mach. Learn. Res. 3: 951-991 (2003) - Koby Crammer, Yoram Singer:
A Family of Additive Online Algorithms for Category Ranking. J. Mach. Learn. Res. 3: 1025-1058 (2003) - Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar:
A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. J. Mach. Learn. Res. 3: 1265-1287 (2003) - George Forman:
An Extensive Empirical Study of Feature Selection Metrics for Text Classification. J. Mach. Learn. Res. 3: 1289-1305 (2003) - Amir Globerson, Naftali Tishby:
Sufficient Dimensionality Reduction. J. Mach. Learn. Res. 3: 1307-1331 (2003) - Isabelle Guyon, André Elisseeff:
An Introduction to Variable and Feature Selection. J. Mach. Learn. Res. 3: 1157-1182 (2003) - Simon Perkins, Kevin Lacker, James Theiler:
Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space. J. Mach. Learn. Res. 3: 1333-1356 (2003) - Alain Rakotomamonjy:
Variable Selection Using SVM-based Criteria. J. Mach. Learn. Res. 3: 1357-1370 (2003) - Juha Reunanen:
Overfitting in Making Comparisons Between Variable Selection Methods. J. Mach. Learn. Res. 3: 1371-1382 (2003) - Isabelle Rivals, Léon Personnaz:
MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling. J. Mach. Learn. Res. 3: 1383-1398 (2003) - Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois, Yacine Oussar:
Ranking a Random Feature for Variable and Feature Selection. J. Mach. Learn. Res. 3: 1399-1414 (2003) - Kari Torkkola:
Feature Extraction by Non-Parametric Mutual Information Maximization. J. Mach. Learn. Res. 3: 1415-1438 (2003) - Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping:
Use of the Zero-Norm with Linear Models and Kernel Methods. J. Mach. Learn. Res. 3: 1439-1461 (2003) - Dmitry Zelenko, Chinatsu Aone, Anthony Richardella:
Kernel Methods for Relation Extraction. J. Mach. Learn. Res. 3: 1083-1106 (2003) - 2002
- András Antos, Balázs Kégl, Tamás Linder, Gábor Lugosi:
Data-dependent margin-based generalization bounds for classification. J. Mach. Learn. Res. 3: 73-98 (2002) - Peter Auer:
Using Confidence Bounds for Exploitation-Exploration Trade-offs. J. Mach. Learn. Res. 3: 397-422 (2002) - Francis R. Bach, Michael I. Jordan:
Kernel Independent Component Analysis. J. Mach. Learn. Res. 3: 1-48 (2002) - Peter L. Bartlett, Shahar Mendelson:
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. J. Mach. Learn. Res. 3: 463-482 (2002) - Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
Limitations of Learning Via Embeddings in Euclidean Half Spaces. J. Mach. Learn. Res. 3: 441-461 (2002) - Hendrik Blockeel, Jan Struyf:
Efficient Algorithms for Decision Tree Cross-validation. J. Mach. Learn. Res. 3: 621-650 (2002) - Olivier Bousquet, Manfred K. Warmuth:
Tracking a Small Set of Experts by Mixing Past Posteriors. J. Mach. Learn. Res. 3: 363-396 (2002) - Ronen I. Brafman, Moshe Tennenholtz:
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning. J. Mach. Learn. Res. 3: 213-231 (2002)
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