JMLR 2004

55 papers

A Compression Approach to Support Vector Model Selection Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf

A Fast Algorithm for Joint Diagonalization with Non-Orthogonal Transformations and Its Application to Blind Source Separation Andreas Ziehe, Pavel Laskov, Guido Nolte, Klaus-Robert Müller

A Geometric Approach to Multi-Criterion Reinforcement Learning Shie Mannor, Nahum Shimkin

A Universal Well-Calibrated Algorithm for On-Line Classification (Special Topic on Learning Theory) Vladimir Vovk

Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods Giorgio Valentini, Thomas G. Dietterich

Boosting as a Regularized Path to a Maximum Margin Classifier Saharon Rosset, Ji Zhu, Trevor Hastie

Computable Shell Decomposition Bounds John Langford, David McAllester

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces Kenji Fukumizu, Francis R. Bach, Michael I. Jordan

Distance-Based Classification with Lipschitz Functions (Special Topic on Learning Theory) Ulrike von Luxburg, Olivier Bousquet

Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces Michael Quist, Golan Yona

Efficient Feature Selection via Analysis of Relevance and Redundancy Lei Yu, Huan Liu

Exact Bayesian Structure Discovery in Bayesian Networks Mikko Koivisto, Kismat Sood

Fast Binary Feature Selection with Conditional Mutual Information François Fleuret

Fast String Kernels Using Inexact Matching for Protein Sequences Christina Leslie, Rui Kuang

Feature Discovery in Non-Metric Pairwise Data Julian Laub, Klaus-Robert Müller

Feature Selection for Unsupervised Learning Jennifer G. Dy, Carla E. Brodley

Generalization Error Bounds for Threshold Decision Lists Martin Anthony

Hierarchical Latent Class Models for Cluster Analysis Nevin L. Zhang

Image Categorization by Learning and Reasoning with Regions Yixin Chen, James Z. Wang

In Defense of One-vs-All Classification Ryan Rifkin, Aldebaro Klautau

Knowledge-Based Kernel Approximation Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild

Large-Sample Learning of Bayesian Networks Is NP-Hard David Maxwell Chickering, David Heckerman, Christopher Meek

Learning Ensembles from Bites: A Scalable and Accurate Approach Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer

Learning the Kernel Matrix with Semidefinite Programming Gert R.G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui, Michael I. Jordan

Lossless Online Bayesian Bagging Herbert K. H. Lee, Merlise A. Clyde

Model Averaging for Prediction with Discrete Bayesian Networks Denver Dash, Gregory F. Cooper

New Techniques for Disambiguation in Natural Language and Their Application to Biological Text Filip Ginter, Jorma Boberg, Jouni Järvinen, Tapio Salakoski

No Unbiased Estimator of the Variance of K-Fold Cross-Validation Yoshua Bengio, Yves Grandvalet

Non-Negative Matrix Factorization with Sparseness Constraints Patrik O. Hoyer

On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition Andreas Christmann, Ingo Steinwart

On the Importance of Small Coordinate Projections Shahar Mendelson, Petra Philips

Online Choice of Active Learning Algorithms Yoram Baram, Ran El Yaniv, Kobi Luz

PAC-Learnability of Probabilistic Deterministic Finite State Automata Alexander Clark, Franck Thollard

Preference Elicitation and Query Learning (Special Topic on Learning Theory) Avrim Blum, Jeffrey Jackson, Tuomas Sandholm, Martin Zinkevich

Probability Estimates for Multi-Class Classification by Pairwise Coupling Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng

Probability Product Kernels (Special Topic on Learning Theory) Tony Jebara, Risi Kondor, Andrew Howard

Randomized Variable Elimination David J. Stracuzzi, Paul E. Utgoff

Rational Kernels: Theory and Algorithms (Special Topic on Learning Theory) Corinna Cortes, Patrick Haffner, Mehryar Mohri

RCV1: A New Benchmark Collection for Text Categorization Research David D. Lewis, Yiming Yang, Tony G. Rose, Fan Li

Reinforcement Learning with Factored States and Actions Brian Sallans, Geoffrey E. Hinton

Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters Isao Higuchi, Shinto Eguchi

Second Order Cone Programming Formulations for Feature Selection Chiranjib Bhattacharyya

Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees Matti Kääriäinen, Tuomo Malinen, Tapio Elomaa

Some Dichotomy Theorems for Neural Learning Problems Michael Schmitt

Some Properties of Regularized Kernel Methods Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri

Sources of Success for Boosted Wrapper Induction David Kauchak, Joseph Smarr, Charles Elkan

Statistical Analysis of Some Multi-Category Large Margin Classification Methods Tong Zhang

Subgroup Discovery with CN2-SD Nada Lavrač, Branko Kavšek, Peter Flach, Ljupčo Todorovski

Support Vector Machine Soft Margin Classifiers: Error Analysis Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou

The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire

The Entire Regularization Path for the Support Vector Machine Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu

The Minimum Error Minimax Probability Machine Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan

The Sample Complexity of Exploration in the Multi-Armed Bandit Problem (Special Topic on Learning Theory) Shie Mannor, John N. Tsitsiklis

Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning Evan Greensmith, Peter L. Bartlett, Jonathan Baxter

Weather Data Mining Using Independent Component Analysis Jayanta Basak, Anant Sudarshan, Deepak Trivedi, M. S. Santhanam