variance reduction

A Non–Convex Optimization Approach to Correlation Clustering AAAI 2019 ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks ICLR 2019 ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables ICML 2019 A Stochastic Composite Gradient Method with Incremental Variance Reduction NeurIPS 2019 Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems AAAI 2019 Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization IJCAI 2019 A unified variance-reduced accelerated gradient method for convex optimization NeurIPS 2019 A Universally Optimal Multistage Accelerated Stochastic Gradient Method NeurIPS 2019 Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator ICML 2019 Continuous-time Models for Stochastic Optimization Algorithms NeurIPS 2019 Control Regularization for Reduced Variance Reinforcement Learning ICML 2019 Credit Assignment Techniques in Stochastic Computation Graphs AISTATS 2019 Curvature-Exploiting Acceleration of Elastic Net Computations ICML 2019 Decentralized Optimization with Edge Sampling IJCAI 2019 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019 Direct Acceleration of SAGA using Sampled Negative Momentum AISTATS 2019 Distributionally Robust Submodular Maximization AISTATS 2019 DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization JMLR 2019 Efficient Counterfactual Learning from Bandit Feedback AAAI 2019 Efficient Training on Very Large Corpora via Gramian Estimation ICLR 2019 Estimate Sequences for Variance-Reduced Stochastic Composite Optimization ICML 2019 Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization AAAI 2019 GO Gradient for Expectation-Based Objectives ICLR 2019 Hamiltonian Monte Carlo with Energy Conserving Subsampling JMLR 2019 Hessian Aided Policy Gradient ICML 2019