"variance reduction" Papers
18 papers found
Conference
Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity
Dmitry Bylinkin, Aleksandr Beznosikov
AAAI 2025paperarXiv:2412.16414
3
citations
Better Estimation of the Kullback--Leibler Divergence Between Language Models
Afra Amini, Tim Vieira, Ryan Cotterell
NEURIPS 2025arXiv:2504.10637
4
citations
Doubly Optimal Policy Evaluation for Reinforcement Learning
Shuze Liu, Claire Chen, Shangtong Zhang
ICLR 2025arXiv:2410.02226
5
citations
Efficient Multi-Policy Evaluation for Reinforcement Learning
Shuze Daniel Liu, Claire Chen, Shangtong Zhang
AAAI 2025paperarXiv:2408.08706
2
citations
Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning
Claire Chen, Shuze Liu, Shangtong Zhang
ICLR 2025arXiv:2410.05655
1
citations
Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
Theo Bourdais, Houman Owhadi
ICLR 2025arXiv:2409.17267
2
citations
On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
Xinwen Zhang, Hongchang Gao
NEURIPS 2025
PseuZO: Pseudo-Zeroth-Order Algorithm for Training Deep Neural Networks
Pengyun Yue, Xuanlin Yang, Mingqing Xiao et al.
NEURIPS 2025
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams et al.
ICLR 2025arXiv:2410.02490
1
citations
Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions
Yuya Hikima, Akiko Takeda
AAAI 2025paperarXiv:2412.20330
3
citations
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
Brett Daley, Martha White, Marlos C. Machado
ICML 2024oralarXiv:2402.03903
5
citations
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang et al.
ICML 2024arXiv:2403.03562
7
citations
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
ICML 2024arXiv:2301.13734
7
citations
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
ICML 2024arXiv:2407.16037
6
citations
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
ICML 2024arXiv:2308.08858
2
citations
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian Stich
ICML 2024arXiv:2403.02967
13
citations
SILVER: Single-loop variance reduction and application to federated learning
Kazusato Oko, Shunta Akiyama, Denny Wu et al.
ICML 2024
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
Chenghan Xie, Chenxi Li, Chuwen Zhang et al.
AAAI 2024paperarXiv:2310.17319
14
citations