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Matthew Shunshi Zhang
Matthew Shunshi Zhang
Verified email at mail.utoronto.ca - Homepage
Title
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Year
Benchmarking model-based reinforcement learning
T Wang, X Bao, I Clavera, J Hoang, Y Wen, E Langlois, S Zhang, G Zhang, ...
arXiv preprint arXiv:1907.02057, 2019
4162019
Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev
S Chewi, MA Erdogdu, MB Li, R Shen, M Zhang
arXiv preprint arXiv:2112.12662, 2021
872021
Towards a theory of non-log-concave sampling: first-order stationarity guarantees for Langevin Monte Carlo
K Balasubramanian, S Chewi, MA Erdogdu, A Salim, S Zhang
Conference on Learning Theory, 2896-2923, 2022
532022
One-shot pruning of recurrent neural networks by jacobian spectrum evaluation
MS Zhang, B Stadie
arXiv preprint arXiv:1912.00120, 2019
362019
Convergence of Langevin Monte Carlo in chi-squared and Rényi divergence
MA Erdogdu, R Hosseinzadeh, S Zhang
International Conference on Artificial Intelligence and Statistics, 8151-8175, 2022
302022
Improved discretization analysis for underdamped Langevin Monte Carlo
S Zhang, S Chewi, M Li, K Balasubramanian, MA Erdogdu
The Thirty Sixth Annual Conference on Learning Theory, 36-71, 2023
242023
Convergence and optimality of policy gradient methods in weakly smooth settings
MS Zhang, MA Erdogdu, A Garg
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 9066-9073, 2022
62022
Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo
T Huix, M Zhang, A Durmus
International Conference on Artificial Intelligence and Statistics, 8749-8770, 2023
22023
Sampling from the Mean-Field Stationary Distribution
Y Kook, MS Zhang, S Chewi, MA Erdogdu, MB Li
arXiv preprint arXiv:2402.07355, 2024
12024
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies
Y Kook, SS Vempala, MS Zhang
arXiv preprint arXiv:2405.01425, 2024
2024
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