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Matthew Shunshi Zhang

Shunshi Zhang 0001

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affiliation: University of Toronto, Canada

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2020 – today

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2024
[i4]
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  - journals/corr/abs-2402-07355
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Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan Bill Li:
Sampling from the Mean-Field Stationary Distribution. CoRR abs/2402.07355 (2024)
2023
[c6]
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  - conf/colt/ZhangCLBE23
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Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu:
Improved Discretization Analysis for Underdamped Langevin Monte Carlo. COLT 2023: 36-71
2022
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  - conf/aaai/ZhangEG22
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Matthew Shunshi Zhang, Murat A. Erdogdu, Animesh Garg:
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. AAAI 2022: 9066-9073
[c4]
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Murat A. Erdogdu, Rasa Hosseinzadeh, Shunshi Zhang:
Convergence of Langevin Monte Carlo in Chi-Squared and Rényi Divergence. AISTATS 2022: 8151-8175
[c3]
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Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang:
Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. COLT 2022: 1-2
[c2]
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Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang:
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. COLT 2022: 2896-2923
2021
[i3]
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  - journals/corr/abs-2111-00185
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Matthew Shunshi Zhang, Murat A. Erdogdu, Animesh Garg:
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings. CoRR abs/2111.00185 (2021)
2020
[c1]
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Matthew Shunshi Zhang, Bradly C. Stadie:
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation. ICLR 2020

2010 – 2019

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2019
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  - journals/corr/abs-1907-02057
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Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba:
Benchmarking Model-Based Reinforcement Learning. CoRR abs/1907.02057 (2019)
[i1]
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  - journals/corr/abs-1912-00120
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Matthew Shunshi Zhang, Bradly C. Stadie:
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation. CoRR abs/1912.00120 (2019)

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