Journal of Machine Learning Research, Volume 5
Volume 5, January 2004
- Gert R. G. Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent El Ghaoui, Michael I. Jordan: Learning the Kernel Matrix with Semidefinite Programming. 27-72
- Kenji Fukumizu, Francis R. Bach, Michael I. Jordan: Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces. 73-99
Volume 5, February 2004
- Nada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski: Subgroup Discovery with CN2-SD. 153-188
- Martin Anthony: Generalization Error Bounds for Threshold Decision Lists. 189-217
Volume 5, March 2004
- Jayanta Basak, Anant Sudarshan, Deepak Trivedi, M. S. Santhanam: Weather Data Mining Using Independent Component Analysis. 239-253
Volume 5, April 2004
- Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf: A Compression Approach to Support Vector Model Selection. 293-323
- David D. Lewis, Yiming Yang, Tony G. Rose, Fan Li: RCV1: A New Benchmark Collection for Text Categorization Research. 361-397
- Michael Quist, Golan Yona: Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces. 399-420
- Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning Ensembles from Bites: A Scalable and Accurate Approach. 421-451
Volume 5, May 2004
- Isao Higuchi, Shinto Eguchi: Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters. 453-471
- Alexander Clark, Franck Thollard: PAC-learnability of Probabilistic Deterministic Finite State Automata. 473-497
- David Kauchak, Joseph Smarr, Charles Elkan: Sources of Success for Boosted Wrapper Induction. 499-527
Volume 5, June 2004
- Vladimir Vovk: A Universal Well-Calibrated Algorithm for On-line Classification. 575-604
- Filip Ginter, Jorma Boberg, Jouni Järvinen, Tapio Salakoski: New Techniques for Disambiguation in Natural Language and Their Application to Biological Text. 605-621
- Shie Mannor, John N. Tsitsiklis: The Sample Complexity of Exploration in the Multi-Armed Bandit Problem. 623-648
- Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich: Preference Elicitation and Query Learning. 649-667
- Ulrike von Luxburg, Olivier Bousquet: Distance-Based Classification with Lipschitz Functions. 669-695
- Nevin Lianwen Zhang: Hierarchical Latent Class Models for Cluster Analysis. 697-723
Volume 5, July 2004
- Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods. 725-775
- Andreas Ziehe, Pavel Laskov, Guido Nolte, Klaus-Robert Müller: A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation. 777-800
Volume 5, August 2004
- Michael Schmitt: Some Dichotomy Theorems for Neural Learning Problems. 891-912
- Saharon Rosset, Ji Zhu, Trevor Hastie: Boosting as a Regularized Path to a Maximum Margin Classifier. 941-973
- Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng: Probability Estimates for Multi-class Classification by Pairwise Coupling. 975-1005
- Andreas Christmann, Ingo Steinwart: On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition. 1007-1034
- Brian Sallans, Geoffrey E. Hinton: Reinforcement Learning with Factored States and Actions. 1063-1088
Volume 5, September 2004
- Yoshua Bengio, Yves Grandvalet: No Unbiased Estimator of the Variance of K-Fold Cross-Validation. 1089-1105
- Matti Kääriäinen, Tuomo Malinen, Tapio Elomaa: Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees. 1107-1126
- Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild: Knowledge-Based Kernel Approximation. 1127-1141
- Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou: Support Vector Machine Soft Margin Classifiers: Error Analysis. 1143-1175
- Denver Dash, Gregory F. Cooper: Model Averaging for Prediction with Discrete Bayesian Networks. 1177-1203
Volume 5, Oktober 2004
- Tong Zhang: Statistical Analysis of Some Multi-Category Large Margin Classification Methods. 1225-1251
- Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan: The Minimum Error Minimax Probability Machine. 1253-1286
- David Maxwell Chickering, David Heckerman, Christopher Meek: Large-Sample Learning of Bayesian Networks is NP-Hard. 1287-1330
- Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri: Some Properties of Regularized Kernel Methods. 1363-1390
- Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu: The Entire Regularization Path for the Support Vector Machine. 1391-1415
Volume 5, November 2004
- Chiranjib Bhattacharyya: Second Order Cone Programming Formulations for Feature Selection. 1417-1433
- Christina S. Leslie, Rui Kuang: Fast String Kernels using Inexact Matching for Protein Sequences. 1435-1455
- Patrik O. Hoyer: Non-negative Matrix Factorization with Sparseness Constraints. 1457-1469
- Evan Greensmith, Peter L. Bartlett, Jonathan Baxter: Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning. 1471-1530
- François Fleuret: Fast Binary Feature Selection with Conditional Mutual Information. 1531-1555
Volume 5, December 2004
- Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire: The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins. 1557-1595
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last updated on 2013-06-18T214307 by the dblp team