variance reduction

Improving Sign Random Projections With Additional Information ICML 2018 Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding NeurIPS 2018 Katyusha: The First Direct Acceleration of Stochastic Gradient Methods JMLR 2018 Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization ICML 2018 Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data ICML 2018 Local Convergence Properties of SAGA/Prox-SVRG and Acceleration ICML 2018 Non-convex Conditional Gradient Sliding ICML 2018 Not All Samples Are Created Equal: Deep Learning with Importance Sampling ICML 2018 On Acceleration with Noise-Corrupted Gradients ICML 2018 Online Variance Reduction for Stochastic Optimization COLT 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 On Truly Block Eigensolvers via Riemannian Optimization AISTATS 2018 Policy Optimization with Second-Order Advantage Information IJCAI 2018 Quasi-Monte Carlo Variational Inference ICML 2018 Reparameterization Gradient for Non-differentiable Models NeurIPS 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning CoRL 2018 Riemannian Stochastic Recursive Gradient Algorithm ICML 2018 SEGA: Variance Reduction via Gradient Sketching NeurIPS 2018 Stochastic Chebyshev Gradient Descent for Spectral Optimization NeurIPS 2018 Stochastic Expectation Maximization with Variance Reduction NeurIPS 2018 Stochastic Nested Variance Reduction for Nonconvex Optimization NeurIPS 2018 Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity NeurIPS 2018 Stochastic Training of Graph Convolutional Networks with Variance Reduction ICML 2018 Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018 Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018