Learning Theory

Frames, Reproducing Kernels, Regularization and Learning JMLR 2005 Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes JMLR 2005 Generalization Bounds for the Area Under the ROC Curve JMLR 2005 Learning from Examples as an Inverse Problem JMLR 2005 Learning with Decision Lists of Data-Dependent Features JMLR 2005 Maximum Margin Algorithms with Boolean Kernels JMLR 2005 Multiclass Boosting for Weak Classifiers JMLR 2005 New Horn Revision Algorithms JMLR 2005 Stability of Randomized Learning Algorithms JMLR 2005 Tutorial on Practical Prediction Theory for Classification JMLR 2005 Universal Algorithms for Learning Theory Part I : Piecewise Constant Functions JMLR 2005 A Compression Approach to Support Vector Model Selection JMLR 2004 A Universal Well-Calibrated Algorithm for On-line Classification JMLR 2004 Computable Shell Decomposition Bounds JMLR 2004 Generalization Error Bounds for Threshold Decision Lists JMLR 2004 No Unbiased Estimator of the Variance of K-Fold Cross-Validation JMLR 2004 Online Choice of Active Learning Algorithms JMLR 2004 On the Importance of Small Coordinate Projections JMLR 2004 PAC-learnability of Probabilistic Deterministic Finite State Automata JMLR 2004 Preference Elicitation and Query Learning JMLR 2004 Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees JMLR 2004 Some Dichotomy Theorems for Neural Learning Problems JMLR 2004 Statistical Analysis of Some Multi-Category Large Margin Classification Methods JMLR 2004 Support Vector Machine Soft Margin Classifiers: Error Analysis JMLR 2004 The Minimum Error Minimax Probability Machine JMLR 2004