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variance reduction

523 papers

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Also known as

VR

Co-occurring keywords

stochastic optimization (1060) stochastic gradient descent (1091) stochastic gradient (296) reinforcement learning (4352) policy gradient (520) nonconvex optimization (316) gradient estimation (150) non-convex optimization (547) importance sampling (318) control variate (54)

Papers

State Relevance for Off-Policy Evaluation ICML 2021
Stochastic Proximal AUC Maximization JMLR 2021
L-SVRG and L-Katyusha with Arbitrary Sampling JMLR 2021
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders NIPS 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning NIPS 2021
Machine Learning for Variance Reduction in Online Experiments NIPS 2021
Strength in Numbers: Averaging and Clustering Effects in Mixture of Experts for Graph-Based Dependency Parsing ACL 2021
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents NIPS 2021
Conditional Poisson Stochastic Beams EMNLP 2021
Dual-Free Stochastic Decentralized Optimization with Variance Reduction NIPS 2020
Stochastic Nested Variance Reduction for Nonconvex Optimization JMLR 2020
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise JMLR 2020
Low-Variance and Zero-Variance Baselines for Extensive-Form Games ICML 2020
Reinforcement Learning When All Actions Are Not Always Available AAAI 2020
Extra-gradient with player sampling for faster convergence in n-player games ICML 2020
SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels ICML 2020
Differentiable Meta-Learning of Bandit Policies NIPS 2020
A Group-Theoretic Framework for Data Augmentation NIPS 2020
Quantized Variational Inference NIPS 2020
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds NIPS 2020
Bandit Samplers for Training Graph Neural Networks NIPS 2020
Approximation Based Variance Reduction for Reparameterization Gradients NIPS 2020