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Learning Theory

5312 directly classified papers

Papers per year

Papers

Support Vector Machine Soft Margin Classifiers: Error Analysis JMLR 2004
Generalization Error Bounds for Threshold Decision Lists JMLR 2004
On the Importance of Small Coordinate Projections JMLR 2004
Statistical Analysis of Some Multi-Category Large Margin Classification Methods JMLR 2004
On the Proper Learning of Axis-Parallel Concepts JMLR 2003
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning JMLR 2003
Extensions to Metric-Based Model Selection JMLR 2003
On Inclusion-Driven Learning of Bayesian Networks JMLR 2003
Smooth Boosting and Learning with Malicious Noise JMLR 2003
Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity JMLR 2003
On the Performance of Kernel Classes JMLR 2003
Generalization Error Bounds for Bayesian Mixture Algorithms JMLR 2003
On the Rate of Convergence of Regularized Boosting Classifiers JMLR 2003
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet JMLR 2003
Relational Learning as Search in a Critical Region JMLR 2003
Sparseness of Support Vector Machines JMLR 2003
Learning Rates for Q-learning JMLR 2003
Ultraconservative Online Algorithms for Multiclass Problems JMLR 2003
An Introduction to Variable and Feature Selection JMLR 2003
Variable Selection Using SVM-based Criteria JMLR 2003
Covering Number Bounds of Certain Regularized Linear Function Classes JMLR 2002
Data-dependent margin-based generalization bounds for classification JMLR 2002
Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries JMLR 2002
Algorithmic Luckiness JMLR 2002
Optimal Structure Identification With Greedy Search JMLR 2002