‪Shengbo Wang‬ - ‪Google Scholar‬

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Co-authors

Jose BlanchetStanford UniversityVerified email at stanford.edu
Nian SiUniversity of Chicago Booth School of BusinessVerified email at chicagobooth.edu
Zhengyuan ZhouDept of Technology, Operations and Statistics at NYU SternVerified email at stern.nyu.edu
Peter W. GlynnProfessor of Management Science and EngineeringVerified email at stanford.edu

Shengbo Wang

Shengbo Wang

Ph.D. candidate, Stanford University

Verified email at stanford.edu

Applied Probability


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A finite sample complexity bound for distributionally robust q-learning S Wang, N Si, J Blanchet, Z Zhou International Conference on Artificial Intelligence and Statistics, 3370-3398, 2023	17	2023
On the foundation of distributionally robust reinforcement learning S Wang, N Si, J Blanchet, Z Zhou arXiv preprint arXiv:2311.09018, 2023	7	2023
Sample complexity of variance-reduced distributionally robust Q-learning S Wang, N Si, J Blanchet, Z Zhou arXiv preprint arXiv:2305.18420, 2023	6	2023
Optimal Sample Complexity of Reinforcement Learning for Uniformly Ergodic Discounted Markov Decision Processes. S Wang, J Blanchet, P Glynn CoRR, 2023	2	2023
Optimal Sample Complexity for Average Reward Markov Decision Processes S Wang, J Blanchet, P Glynn arXiv preprint arXiv:2310.08833, 2023		2023

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