Optimization

Estimating Functions for Blind Separation When Sources Have Variance Dependencies JMLR 2005 Estimation of Non-Normalized Statistical Models by Score Matching JMLR 2005 Fast Kernel Classifiers with Online and Active Learning JMLR 2005 Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach JMLR 2005 Large Margin Methods for Structured and Interdependent Output Variables JMLR 2005 Learning the Kernel Function via Regularization JMLR 2005 Managing Diversity in Regression Ensembles JMLR 2005 Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection JMLR 2005 Multiclass Classification with Multi-Prototype Support Vector Machines JMLR 2005 Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial JMLR 2005 Toward Optimal Configuration Space Sampling RSS 2005 Working Set Selection Using Second Order Information for Training Support Vector Machines JMLR 2005 A Geometric Approach to Multi-Criterion Reinforcement Learning JMLR 2004 Boosting as a Regularized Path to a Maximum Margin Classifier JMLR 2004 Knowledge-Based Kernel Approximation JMLR 2004 Learning the Kernel Matrix with Semidefinite Programming JMLR 2004 On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition JMLR 2004 Some Properties of Regularized Kernel Methods JMLR 2004 The Entire Regularization Path for the Support Vector Machine JMLR 2004 An Efficient Boosting Algorithm for Combining Preferences JMLR 2003 Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation JMLR 2003 Blind Source Recovery: A Framework in the State Space JMLR 2003 Extensions to Metric-Based Model Selection JMLR 2003 Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space JMLR 2003 Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity JMLR 2003