Ming Yin - RankMe

50 papers A* 16A 4B 1Journal 28Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Genome-Bench: A Scientific Reasoning Benchmark from Real-World Expert Discussions. CoRR Ming Yin, Yuanhao Qu, Dyllan Liu, Ling Yang, Le Cong, Mengdi Wang
2025	A*	`conf`	MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations. ICML Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang
2025	J	`jnl`	MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations. CoRR Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang
2025	J	`jnl`	No-Regret Linear Bandits under Gap-Adjusted Misspecification. CoRR Chong Liu, Dan Qiao, Ming Yin, Ilija Bogunovic, Yuxiang Wang
2025	J	`jnl`	On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures. CoRR Ming Yin, Mengdi Wang, Yuxiang Wang
2025	—	`conf`	Rates for Offline Reinforcement Learning with Adaptively Collected Data. L4DC Sunil Madhow, Dan Qiao, Ming Yin, Yuxiang Wang
2024	A*	`conf`	A Theoretical Perspective for Speculative Decoding Algorithm. NeurIPS Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang
2024	J	`jnl`	A Theoretical Perspective for Speculative Decoding Algorithm. CoRR Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang
2024	A*	`conf`	Fast Best-of-N Decoding via Speculative Rejection. NeurIPS Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette
2024	J	`jnl`	Fast Best-of-N Decoding via Speculative Rejection. CoRR Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette
2024	A*	`conf`	Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games. ICML Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	A*	`conf`	NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation. NeurIPS Momin Haider, Ming Yin, Menglei Zhang, Arpit Gupta, Jing Zhu, Yuxiang Wang
2024	J	`jnl`	NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation. CoRR Momin Haider, Ming Yin, Menglei Zhang, Arpit Gupta, Jing Zhu, Yuxiang Wang
2024	A*	`conf`	Offline Multitask Representation Learning for Reinforcement Learning. NeurIPS Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup
2024	J	`jnl`	Offline Multitask Representation Learning for Reinforcement Learning. CoRR Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup
2024	J	`jnl`	Relative-Translation Invariant Wasserstein Distance. CoRR Binshuai Wang, Qiwei Di, Ming Yin, Mengdi Wang, Quanquan Gu, Peng Wei
2024	J	`jnl`	Toward General Function Approximation in Nonstationary Reinforcement Learning. IEEE J. Sel. Areas Inf. Theory Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	B	`conf`	Towards General Function Approximation in Nonstationary Reinforcement Learning. ISIT Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	J	`jnl`	Transfer Q Star: Principled Decoding for LLM Alignment. CoRR Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang
2024	A*	`conf`	Transfer Q-star : Principled Decoding for LLM Alignment. NeurIPS Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang
2023	J	`jnl`	Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs. CoRR Dan Qiao, Ming Yin, Yu-Xiang Wang
2023	J	`jnl`	Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games. CoRR Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	A	`conf`	No-Regret Linear Bandits beyond Realizability. UAI Chong Liu, Ming Yin, Yu-Xiang Wang
2023	J	`jnl`	No-Regret Linear Bandits beyond Realizability. CoRR Chong Liu, Ming Yin, Yu-Xiang Wang
2023	A*	`conf`	Non-stationary Reinforcement Learning under General Function Approximation. ICML Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	J	`jnl`	Non-stationary Reinforcement Learning under General Function Approximation. CoRR Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	J	`jnl`	Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data. CoRR Sunil Madhow, Dan Xiao, Ming Yin, Yu-Xiang Wang
2023	A*	`conf`	Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. ICML Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang
2023	A*	`conf`	Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. ICLR Ming Yin, Mengdi Wang, Yu-Xiang Wang
2023	A*	`conf`	Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. NeurIPS Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma
2023	J	`jnl`	Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. CoRR Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yi-An Ma
2022	A*	`conf`	Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. ICLR Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang
2022	J	`jnl`	Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. CoRR Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang
2022	J	`jnl`	Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. CoRR Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang
2022	J	`jnl`	Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. CoRR Ming Yin, Mengdi Wang, Yu-Xiang Wang
2022	J	`jnl`	Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality. CoRR Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang
2022	A	`conf`	Offline stochastic shortest path: Learning, evaluation and towards optimality. UAI Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang
2022	A*	`conf`	Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost. ICML Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang
2022	J	`jnl`	Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost. CoRR Dan Qiao, Ming Yin, Ming Min, Yu-Xiang Wang
2022	J	`jnl`	Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks. CoRR Kaiqi Zhang, Ming Yin, Yu-Xiang Wang
2021	A*	`conf`	Near-Optimal Offline Reinforcement Learning via Double Variance Reduction. NeurIPS Ming Yin, Yu Bai, Yu-Xiang Wang
2021	J	`jnl`	Near-Optimal Offline Reinforcement Learning via Double Variance Reduction. CoRR Ming Yin, Yu Bai, Yu-Xiang Wang
2021	A	`conf`	Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning. AISTATS Ming Yin, Yu Bai, Yu-Xiang Wang
2021	A*	`conf`	Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings. NeurIPS Ming Yin, Yu-Xiang Wang
2021	J	`jnl`	Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings. CoRR Ming Yin, Yu-Xiang Wang
2021	A*	`conf`	Towards Instance-Optimal Offline Reinforcement Learning with Pessimism. NeurIPS Ming Yin, Yu-Xiang Wang
2021	J	`jnl`	Towards Instance-Optimal Offline Reinforcement Learning with Pessimism. CoRR Ming Yin, Yu-Xiang Wang
2020	A	`conf`	Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. AISTATS Ming Yin, Yu-Xiang Wang
2020	J	`jnl`	Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning. CoRR Ming Yin, Yu-Xiang Wang
2020	J	`jnl`	Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning. CoRR Ming Yin, Yu Bai, Yu-Xiang Wang