Optimization

Active learning of neural response functions with Gaussian processes NeurIPS 2011 Adaptive Hedge NeurIPS 2011 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011 A Denoising View of Matrix Completion NeurIPS 2011 Advice Refinement in Knowledge-Based SVMs NeurIPS 2011 A Family of Simple Non-Parametric Kernel Learning Algorithms JMLR 2011 A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods AISTATS 2011 A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems AISTATS 2011 A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences COLT 2011 Algorithms and hardness results for parallel large margin learning NeurIPS 2011 Algorithms for Hyper-Parameter Optimization NeurIPS 2011 Analysis and Improvement of Policy Gradient Estimation NeurIPS 2011 An Exact Algorithm for F-Measure Maximization NeurIPS 2011 Approximate Model Selection for Large Scale LSSVM ACML 2011 Approximating Semidefinite Programs in Sublinear Time NeurIPS 2011 A Serial Approach to Handling High-Dimensional Measurements in the Sigma-Point Kalman Filter RSS 2011 Automatic Calibration of Multiple Coplanar Sensors RSS 2011 Beating SGD: Learning SVMs in Sublinear Time NeurIPS 2011 Better Algorithms for Benign Bandits JMLR 2011 Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts NeurIPS 2011 Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011 Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011 Budgeted Optimization with Concurrent Stochastic-Duration Experiments NeurIPS 2011 Clustered Multi-Task Learning Via Alternating Structure Optimization NeurIPS 2011