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ORCIDMing Yin 0003
Person information
- affiliation: University of California, Santa Barbara, CA, USA
Other persons with the same name
- Ming Yin — disambiguation page
- Ming Yin 0001
![[0000-0002-7364-139X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-7364-139X")
— Purdue University, West Lafayette, IN, USA - Ming Yin 0002 — Guangdong University of Technology, School of Automation, Guangzhou, China (and 1 more)
- Ming Yin 0004 — Sichuan University, Chengdu, China
- Ming Yin 0005 — Northweastern Polytechnology University, Xi'an, China
- Ming Yin 0006 — University of Science and Technology of China, Hefei, China
- Ming Yin 0007 — Chengdu University of Technology, Chengdu, China
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2020 – today
- 2024
[j1]Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Toward General Function Approximation in Nonstationary Reinforcement Learning. IEEE J. Sel. Areas Inf. Theory 5: 190-206 (2024)- [c15]Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games. ICML 2024 - [c14]Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Towards General Function Approximation in Nonstationary Reinforcement Learning. ISIT 2024: 1-6 - [i20]Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup:
Offline Multitask Representation Learning for Reinforcement Learning. CoRR abs/2403.11574 (2024) - [i19]Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang:
Transfer Q Star: Principled Decoding for LLM Alignment. CoRR abs/2405.20495 (2024) - [i18]Binshuai Wang, Qiwei Di, Ming Yin, Mengdi Wang, Quanquan Gu, Peng Wei:
Relative-Translation Invariant Wasserstein Distance. CoRR abs/2409.02416 (2024) - 2023
- [c13]Ming Yin, Mengdi Wang, Yu-Xiang Wang:
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. ICLR 2023 - [c12]Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Non-stationary Reinforcement Learning under General Function Approximation. ICML 2023: 9976-10007 - [c11]Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang:
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. ICML 2023: 20485-20528 - [c10]Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. NeurIPS 2023 - [c9]Chong Liu, Ming Yin, Yu-Xiang Wang:
No-Regret Linear Bandits beyond Realizability. UAI 2023: 1294-1303 - [i17]Dan Qiao, Ming Yin, Yu-Xiang Wang:
Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs. CoRR abs/2302.12456 (2023) - [i16]Chong Liu, Ming Yin, Yu-Xiang Wang:
No-Regret Linear Bandits beyond Realizability. CoRR abs/2302.13252 (2023) - [i15]Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Non-stationary Reinforcement Learning under General Function Approximation. CoRR abs/2306.00861 (2023) - [i14]Sunil Madhow, Dan Xiao, Ming Yin, Yu-Xiang Wang:
Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data. CoRR abs/2306.14063 (2023) - [i13]Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games. CoRR abs/2308.08858 (2023) - [i12]Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yi-An Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. CoRR abs/2310.18919 (2023) - 2022
- [c8]Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang:
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. ICLR 2022 - [c7]Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang:
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost. ICML 2022: 18031-18061 - [c6]Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang:
Offline stochastic shortest path: Learning, evaluation and towards optimality. UAI 2022: 2278-2288 - [i11]Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang:
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost. CoRR abs/2202.06385 (2022) - [i10]Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang:
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. CoRR abs/2203.05804 (2022) - [i9]Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang:
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality. CoRR abs/2206.04921 (2022) - [i8]Kaiqi Zhang, Ming Yin, Yu-Xiang Wang:
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks. CoRR abs/2206.05916 (2022) - [i7]Ming Yin, Mengdi Wang, Yu-Xiang Wang:
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. CoRR abs/2210.00750 (2022) - [i6]Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang:
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. CoRR abs/2211.15956 (2022) - 2021
- [c5]Ming Yin, Yu Bai, Yu-Xiang Wang:
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning. AISTATS 2021: 1567-1575 - [c4]Ming Yin, Yu-Xiang Wang:
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism. NeurIPS 2021: 4065-4078 - [c3]Ming Yin, Yu Bai, Yu-Xiang Wang:
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction. NeurIPS 2021: 7677-7688 - [c2]Ming Yin, Yu-Xiang Wang:
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings. NeurIPS 2021: 12890-12903 - [i5]Ming Yin, Yu Bai, Yu-Xiang Wang:
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction. CoRR abs/2102.01748 (2021) - [i4]Ming Yin, Yu-Xiang Wang:
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings. CoRR abs/2105.06029 (2021) - [i3]Ming Yin, Yu-Xiang Wang:
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism. CoRR abs/2110.08695 (2021) - 2020
- [c1]Ming Yin, Yu-Xiang Wang:
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. AISTATS 2020: 3948-3958 - [i2]Ming Yin, Yu-Xiang Wang:
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. CoRR abs/2001.10742 (2020) - [i1]Ming Yin, Yu Bai, Yu-Xiang Wang:
Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning. CoRR abs/2007.03760 (2020)
Coauthor Index
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