Optimization

Stochastic convex optimization with bandit feedback NeurIPS 2011 Stochastic Methods for -regularized Loss Minimization JMLR 2011 Structured sparse coding via lateral inhibition NeurIPS 2011 Structured Variable Selection with Sparsity-Inducing Norms JMLR 2011 Structure Learning for Optimization NeurIPS 2011 Submodular Multi-Label Learning NeurIPS 2011 TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning NeurIPS 2011 The Fast Convergence of Boosting NeurIPS 2011 The Rate of Convergence of Adaboost COLT 2011 Thinning Measurement Models and Questionnaire Design NeurIPS 2011 Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm AISTATS 2011 Trace Lasso: a trace norm regularization for correlated designs NeurIPS 2011 Training SVMs Without Offset JMLR 2011 Two-Layer Multiple Kernel Learning AISTATS 2011 Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NeurIPS 2011 Universal low-rank matrix recovery from Pauli measurements NeurIPS 2011 Variable Sparsity Kernel Learning JMLR 2011 Accounting for network effects in neuronal responses using L1 regularized point process models NeurIPS 2010 A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification JMLR 2010 Active Instance Sampling via Matrix Partition NeurIPS 2010 Active Learning by Querying Informative and Representative Examples NeurIPS 2010 A Dirty Model for Multi-task Learning NeurIPS 2010 A Family of Penalty Functions for Structured Sparsity NeurIPS 2010 A Fast Hybrid Algorithm for Large-Scale -Regularized Logistic Regression JMLR 2010 An analysis on negative curvature induced by singularity in multi-layer neural-network learning NeurIPS 2010