Glynn, Peter

8 publications

ICML 2025 Tightening Causal Bounds via Covariate-Aware Optimal Transport Sirui Lin, Zijun Gao, Jose Blanchet, Peter Glynn

NeurIPS 2024 An Efficient High-Dimensional Gradient Estimator for Stochastic Differential Equations Shengbo Wang, Jose Blanchet, Peter Glynn

NeurIPS 2024 Deep Learning for Computing Convergence Rates of Markov Chains Yanlin Qu, Jose Blanchet, Peter Glynn

ICLR 2024 Optimal Sample Complexity for Average Reward Markov Decision Processes Shengbo Wang, Jose Blanchet, Peter Glynn

AISTATS 2021 Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning Zhengqing Zhou, Zhengyuan Zhou, Qinxun Bai, Linhai Qiu, Jose Blanchet, Peter Glynn

ALT 2020 Optimal $δ$-Correct Best-Arm Selection for Heavy-Tailed Distributions Shubhada Agrawal, Sandeep Juneja, Peter Glynn

ICML 2019 Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning Casey Chu, Jose Blanchet, Peter Glynn

ICML 2018 Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei