variance reduction

Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization ICML 2020 Importance Sampling Techniques for Policy Optimization JMLR 2020 Linearly Converging Error Compensated SGD NeurIPS 2020 Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020 Lower Bounds and Optimal Algorithms for Personalized Federated Learning NeurIPS 2020 Low-Variance and Zero-Variance Baselines for Extensive-Form Games ICML 2020 Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020 Momentum-Based Policy Gradient Methods ICML 2020 Monte Carlo Gradient Estimation in Machine Learning JMLR 2020 Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL IJCAI 2020 On the Convergence of SARAH and Beyond AISTATS 2020 On the Variance of the Adaptive Learning Rate and Beyond ICLR 2020 Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds NeurIPS 2020 Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks NeurIPS 2020 Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020 ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization JMLR 2020 Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020 Quantized Variational Inference NeurIPS 2020 Random Reshuffling: Simple Analysis with Vast Improvements NeurIPS 2020 Reanalysis of Variance Reduced Temporal Difference Learning ICLR 2020 Reinforcement Learning When All Actions Are Not Always Available AAAI 2020 Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction NeurIPS 2020 Sample Efficient Policy Gradient Methods with Recursive Variance Reduction ICLR 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020 Self-Guided Evolution Strategies with Historical Estimated Gradients IJCAI 2020