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Ming Yin
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
X Yue, Y Ni, K Zhang, T Zheng, R Liu, G Zhang, S Stevens, D Jiang, ...
(CVPR Oral) Conference on Computer Vision and Pattern Recognition, 2024
912024
Near-optimal provable uniform convergence in offline policy evaluation for reinforcement learning
M Yin, Y Bai, YX Wang
(AISTATS oral) International Conference on Artificial Intelligence and …, 2021
87*2021
Towards instance-optimal offline reinforcement learning with pessimism
M Yin, YX Wang
(NeurIPS) Advances in neural information processing systems 34, 4065-4078, 2021
792021
Near-optimal offline reinforcement learning with linear representation: Leveraging variance information with pessimism
M Yin, Y Duan, M Wang, YX Wang
(ICLR) Internation Conference on Learning Representations, 2022, 2022
732022
Asymptotically efficient off-policy evaluation for tabular reinforcement learning
M Yin, YX Wang
(AISTATS) International Conference on Artificial Intelligence and Statistics …, 2020
722020
Near-optimal offline reinforcement learning via double variance reduction
M Yin, Y Bai, YX Wang
(NeurIPS) Advances in neural information processing systems 34, 7677-7688, 2021
702021
Theoremqa: A theorem-driven question answering dataset
W Chen, M Yin, M Ku, P Lu, Y Wan, X Ma, J Xu, X Wang, T Xia
(EMNLP) Empirical Methods in Natural Language Processing, 2023
432023
Optimal uniform ope and model-based offline reinforcement learning in time-homogeneous, reward-free and task-agnostic settings
M Yin, YX Wang
(NeurIPS) Advances in neural information processing systems 34, 12890-12903, 2021
262021
Sample-efficient reinforcement learning with loglog (t) switching cost
D Qiao, M Yin, M Min, YX Wang
(ICML) International Conference on Machine Learning, 18031-18061, 2022
252022
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh, R Arora
(AAAI) AAAI Conference on Artificial Intelligence, 2023, 2023
142023
Offline reinforcement learning with differentiable function approximation is provably efficient
M Yin, M Wang, YX Wang
(ICLR) Internation Conference on Learning Representations, 2023, 2023
142023
Logarithmic switching cost in reinforcement learning beyond linear mdps
D Qiao, M Yin, YX Wang
(ISIT) IEEE International Symposium on Information Theory, 2024
62024
Non-stationary Reinforcement Learning under General Function Approximation
S Feng, M Yin, R Huang, YX Wang, J Yang, Y Liang
(ICML) International Conference on Machine Learning, 2023
52023
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality
M Yin, W Chen, M Wang, YX Wang
(UAI) The 38th Conference on Uncertainty in Artificial Intelligence, 2022
52022
No-Regret Linear Bandits beyond Realizability
C Liu, M Yin, YX Wang
(UAI) The 39th Conference on Uncertainty in Artificial Intelligence, 2023
42023
Why quantization improves generalization: Ntk of binary weight neural networks
K Zhang, M Yin, YX Wang
ICML workshop in Neural Compression, 2023
32023
Offline Multitask Representation Learning for Reinforcement Learning
H Ishfaq*, T Nguyen-Tang, S Feng, R Arora, M Wang, M Yin*, D Precup*
arXiv preprint arXiv:2403.11574, 2024
22024
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
M Yin*, NL Kuang*, M Wang, YX Wang, YA Ma
(NeurIPS) Advances in neural information processing systems, 2023, 2023
22023
Offline Reinforcement Learning with Closed-form Policy Improvement Operators
J Li, E Zhang, M Yin, B Qinxun, YX Wang, WY Wang
(ICML) International Conference on Machine Learning, 2023
22023
Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data
S Madhow, D Xiao, M Yin, YX Wang
3rd Offline RL Workshop: Offline RL as a''Launchpad'', 2022
22022
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Articles 1–20