stochastic optimization

Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function NeurIPS 2012 A Stochastic Bandit Algorithm for Scratch Games ACML 2012 Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit AISTATS 2012 Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NeurIPS 2012 Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning JMLR 2012 Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 Optimal Distributed Online Prediction Using Mini-Batches JMLR 2012 Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 Relax and Randomize : From Value to Algorithms NeurIPS 2012 Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds NeurIPS 2012 Risk-Aversion in Multi-armed Bandits NeurIPS 2012 Scalable Inference of Overlapping Communities NeurIPS 2012 Statistical Optimization in High Dimensions AISTATS 2012 Stochastic Bandit Based on Empirical Moments AISTATS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011 A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences COLT 2011 -Armed Bandits JMLR 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 the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011