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ORCIDJournal of Machine Learning Research, Volume 5
Volume 5, January 2004
- Eyal Even-Dar, Yishay Mansour:
Learning Rates for Q-learning. 1-25 - 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 - Ryan M. Rifkin, Aldebaro Klautau:
In Defense of One-Vs-All Classification. 101-141
Volume 5, February 2004
- Herbert K. H. Lee, Merlise A. Clyde:
Lossless Online Bayesian Bagging. 143-151 - 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
- Shahar Mendelson, Petra Philips:
On the Importance of Small Coordinate Projections. 219-238 - Jayanta Basak, Anant Sudarshan, Deepak Trivedi, M. S. Santhanam:
Weather Data Mining Using Independent Component Analysis. 239-253 - Yoram Baram, Ran El-Yaniv, Kobi Luz:
Online Choice of Active Learning Algorithms. 255-291
Volume 5, April 2004
- Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf:
A Compression Approach to Support Vector Model Selection. 293-323 - Shie Mannor, Nahum Shimkin:
A Geometric Approach to Multi-Criterion Reinforcement Learning. 325-360 - 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 - John Langford, David A. McAllester:
Computable Shell Decomposition Bounds. 529-547 - Mikko Koivisto, Kismat Sood:
Exact Bayesian Structure Discovery in Bayesian Networks. 549-573
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 - Julian Laub, Klaus-Robert Müller:
Feature Discovery in Non-Metric Pairwise Data. 801-818 - Tony Jebara, Risi Kondor, Andrew G. Howard:
Probability Product Kernels. 819-844
Volume 5, August 2004
- Jennifer G. Dy, Carla E. Brodley:
Feature Selection for Unsupervised Learning. 845-889 - Michael Schmitt:
Some Dichotomy Theorems for Neural Learning Problems. 891-912 - Yixin Chen, James Ze Wang:
Image Categorization by Learning and Reasoning with Regions. 913-939 - 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 - Corinna Cortes, Patrick Haffner, Mehryar Mohri:
Rational Kernels: Theory and Algorithms. 1035-1062 - 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
- Lei Yu, Huan Liu:
Efficient Feature Selection via Analysis of Relevance and Redundancy. 1205-1224 - 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 - David J. Stracuzzi, Paul E. Utgoff:
Randomized Variable Elimination. 1331-1362 - 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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