stochastic optimization

Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization ICML 2015 Stochastic Structured Variational Inference AISTATS 2015 Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits AISTATS 2015 Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning NeurIPS 2015 Accelerated Mini-batch Randomized Block Coordinate Descent Method NeurIPS 2014 Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization ICML 2014 Adaptive Monte Carlo via Bandit Allocation ICML 2014 A Filtering Approach to Stochastic Variational Inference NeurIPS 2014 An Accelerated Proximal Coordinate Gradient Method NeurIPS 2014 A second-order bound with excess losses COLT 2014 Beyond the Regret Minimization Barrier: Optimal Algorithms for Stochastic Strongly-Convex Optimization JMLR 2014 Black Box Variational Inference AISTATS 2014 Communication-Efficient Distributed Dual Coordinate Ascent NeurIPS 2014 Communication-Efficient Distributed Optimization using an Approximate Newton-type Method ICML 2014 Extremal Mechanisms for Local Differential Privacy NeurIPS 2014 Fast Stochastic Alternating Direction Method of Multipliers ICML 2014 Finito: A faster, permutable incremental gradient method for big data problems ICML 2014 Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data AISTATS 2014 Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NeurIPS 2014 Large-scale L-BFGS using MapReduce NeurIPS 2014 Learning without concentration COLT 2014 Logistic Regression: Tight Bounds for Stochastic and Online Optimization COLT 2014 Multi-period Trading Prediction Markets with Connections to Machine Learning ICML 2014 Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition NeurIPS 2014 Natural Evolution Strategies JMLR 2014