stochastic optimization

Trajectory-Based Off-Policy Deep Reinforcement Learning ICML 2019 Unifying the Stochastic and the Adversarial Bandits with Knapsack IJCAI 2019 UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization NeurIPS 2019 Variance-based Regularization with Convex Objectives JMLR 2019 Variational Implicit Processes ICML 2019 Variational Noise-Contrastive Estimation AISTATS 2019 A Block Coordinate Ascent Algorithm for Mean-Variance Optimization NeurIPS 2018 Accelerated Stochastic Power Iteration AISTATS 2018 Adaptation to Easy Data in Prediction with Limited Advice NeurIPS 2018 Adaptive Methods for Nonconvex Optimization NeurIPS 2018 Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NeurIPS 2018 A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning ICML 2018 A Generic Approach for Accelerating Stochastic Zeroth-Order Convex Optimization IJCAI 2018 A PID Controller Approach for Stochastic Optimization of Deep Networks CVPR 2018 A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates ICML 2018 Asymptotic optimality of adaptive importance sampling NeurIPS 2018 Asynchronous Doubly Stochastic Group Regularized Learning AISTATS 2018 Bandits with Delayed, Aggregated Anonymous Feedback ICML 2018 Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice JMLR 2018 Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap AISTATS 2018 Contextual Bandits with Stochastic Experts AISTATS 2018 Coordinate Descent with Bandit Sampling NeurIPS 2018 Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces IJCAI 2018 Differentially Private Contextual Linear Bandits NeurIPS 2018 Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization NeurIPS 2018