ICML 2024 "variance reduction" Papers
7 papers found
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
Brett Daley, Martha White, Marlos C. Machado
ICML 2024oralarXiv:2402.03903
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang et al.
ICML 2024posterarXiv:2403.03562
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
ICML 2024posterarXiv:2301.13734
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
ICML 2024posterarXiv:2407.16037
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
ICML 2024posterarXiv:2308.08858
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian Stich
ICML 2024posterarXiv:2403.02967
SILVER: Single-loop variance reduction and application to federated learning
Kazusato Oko, Shunta Akiyama, Denny Wu et al.
ICML 2024poster