JMLR 2004

55 papers

The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins

Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire

Fast Binary Feature Selection with Conditional Mutual Information

Francois Fleuret

Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning

Evan Greensmith, Peter L. Bartlett, Jonathan Baxter

Non-negative Matrix Factorization with Sparseness Constraints

Patrik O. Hoyer

Fast String Kernels using Inexact Matching for Protein Sequences

Christina Leslie, Rui Kuang

Second Order Cone Programming Formulations for Feature Selection

Chiranjib Bhattacharyya

The Entire Regularization Path for the Support Vector Machine

Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu

Some Properties of Regularized Kernel Methods

Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri

Randomized Variable Elimination

David J. Stracuzzi, Paul E. Utgoff

Large-Sample Learning of Bayesian Networks is NP-Hard

David Maxwell Chickering, David Heckerman, Christopher Meek

The Minimum Error Minimax Probability Machine

Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan

Statistical Analysis of Some Multi-Category Large Margin Classification Methods

Tong Zhang

Efficient Feature Selection via Analysis of Relevance and Redundancy

Lei Yu, Huan Liu

Model Averaging for Prediction with Discrete Bayesian Networks

Denver Dash, Gregory F. Cooper

Support Vector Machine Soft Margin Classifiers: Error Analysis

Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou

Knowledge-Based Kernel Approximation

Olvi L. Mangasarian, Jude W. Shavlik, Edward W. Wild

Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees

Matti Kääriäinen, Tuomo Malinen, Tapio Elomaa

No Unbiased Estimator of the Variance of K-Fold Cross-Validation

Yoshua Bengio, Yves Grandvalet

Reinforcement Learning with Factored States and Actions

Brian Sallans, Geoffrey E. Hinton

Rational Kernels: Theory and Algorithms

Corinna Cortes, Patrick Haffner, Mehryar Mohri

On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition

Andreas Christmann, Ingo Steinwart

Probability Estimates for Multi-class Classification by Pairwise Coupling

Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng

Boosting as a Regularized Path to a Maximum Margin Classifier

Saharon Rosset, Ji Zhu, Trevor Hastie

Image Categorization by Learning and Reasoning with Regions

Yixin Chen, James Z. Wang

Some Dichotomy Theorems for Neural Learning Problems

Michael Schmitt

Feature Selection for Unsupervised Learning

Jennifer G. Dy, Carla E. Brodley

Probability Product Kernels

Tony Jebara, Risi Kondor, Andrew Howard

Feature Discovery in Non-Metric Pairwise Data

Julian Laub, Klaus-Robert Müller

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

Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods

Giorgio Valentini, Thomas G. Dietterich

Hierarchical Latent Class Models for Cluster Analysis

Nevin L. Zhang

Distance-Based Classification with Lipschitz Functions

Ulrike Von Luxburg, Olivier Bousquet

Preference Elicitation and Query Learning

Avrim Blum, Jeffrey Jackson, Tuomas Sandholm, Martin Zinkevich

The Sample Complexity of Exploration in the Multi-Armed Bandit Problem

Shie Mannor, John N. Tsitsiklis

New Techniques for Disambiguation in Natural Language and Their Application to Biological Text

Filip Ginter, Jorma Boberg, Jouni Järvinen, Tapio Salakoski

A Universal Well-Calibrated Algorithm for On-line Classification

Vladimir Vovk

Exact Bayesian Structure Discovery in Bayesian Networks

Mikko Koivisto, Kismat Sood

Computable Shell Decomposition Bounds

John Langford, David Mcallester

Sources of Success for Boosted Wrapper Induction

David Kauchak, Joseph Smarr, Charles Elkan

PAC-learnability of Probabilistic Deterministic Finite State Automata

Alexander Clark, Franck Thollard

Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters

Isao Higuchi, Shinto Eguchi

Learning Ensembles from Bites: A Scalable and Accurate Approach

Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer

Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces

Michael Quist, Golan Yona

RCV1: A New Benchmark Collection for Text Categorization Research

David D. Lewis, Yiming Yang, Tony G. Rose, Fan Li

A Geometric Approach to Multi-Criterion Reinforcement Learning

Shie Mannor, Nahum Shimkin

A Compression Approach to Support Vector Model Selection

Ulrike Von Luxburg, Olivier Bousquet, Bernhard Schölkopf

Online Choice of Active Learning Algorithms

Yoram Baram, Ran El Yaniv, Kobi Luz

Weather Data Mining Using Independent Component Analysis

Jayanta Basak, Anant Sudarshan, Deepak Trivedi, M. S. Santhanam

On the Importance of Small Coordinate Projections

Shahar Mendelson, Petra Philips

Generalization Error Bounds for Threshold Decision Lists

Martin Anthony

Subgroup Discovery with CN2-SD

Nada Lavrač, Branko Kavšek, Peter Flach, Ljupčo Todorovski

Lossless Online Bayesian Bagging

Herbert K. H. Lee, Merlise A. Clyde

In Defense of One-Vs-All Classification

Ryan Rifkin, Aldebaro Klautau

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan

Learning the Kernel Matrix with Semidefinite Programming

Gert R.G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui, Michael I. Jordan