convex optimization

Active learning for misspecified generalized linear models NeurIPS 2006 A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006 An Efficient Implementation of an Active Set Method for SVMs JMLR 2006 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006 Convex Repeated Games and Fenchel Duality NeurIPS 2006 Efficient sparse coding algorithms NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 Large Margin Hidden Markov Models for Automatic Speech Recognition NeurIPS 2006 Large Scale Multiple Kernel Learning JMLR 2006 Linearly-solvable Markov decision problems NeurIPS 2006 Max-margin classification of incomplete data NeurIPS 2006 Multi-Task Feature Learning NeurIPS 2006 No-regret Algorithms for Online Convex Programs NeurIPS 2006 Structured Prediction, Dual Extragradient and Bregman Projections JMLR 2006 Learning the Kernel Function via Regularization JMLR 2005 A Robust Minimax Approach to Classification JMLR 2002 Efficient SVM Training Using Low-Rank Kernel Representations JMLR 2001 Lagrangian Support Vector Machines JMLR 2001