Ming Yin

Affiliations:

University of California, Santa Barbara, CA, USA

According to our database¹, Ming Yin authored at least 24 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2024

Toward General Function Approximation in Nonstationary Reinforcement Learning.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2024

Relative-Translation Invariant Wasserstein Distance.

[BibT_eX]

[DOI]

CoRR, 2024

Transfer Q Star: Principled Decoding for LLM Alignment.

[BibT_eX]

[DOI]

CoRR, 2024

Offline Multitask Representation Learning for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Towards General Function Approximation in Nonstationary Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2024

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games.

[BibT_eX]

[DOI]

CoRR, 2023

Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data.

[BibT_eX]

[DOI]

CoRR, 2023

Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs.

[BibT_eX]

[DOI]

Dan Qiao

Ming Yin

Yu-Xiang Wang

CoRR, 2023

No-Regret Linear Bandits beyond Realizability.

[BibT_eX]

[DOI]

Chong Liu

Ming Yin

Yu-Xiang Wang

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Offline Reinforcement Learning with Closed-Form Policy Improvement Operators.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Non-stationary Reinforcement Learning under General Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient.

[BibT_eX]

[DOI]

Ming Yin

Mengdi Wang

Yu-Xiang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks.

[BibT_eX]

[DOI]

Kaiqi Zhang

Ming Yin

Yu-Xiang Wang

CoRR, 2022

Offline stochastic shortest path: Learning, evaluation and towards optimality.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings.

[BibT_eX]

[DOI]

Ming Yin

Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Instance-Optimal Offline Reinforcement Learning with Pessimism.

[BibT_eX]

[DOI]

Ming Yin

Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction.

[BibT_eX]

[DOI]

Ming Yin

Yu Bai

Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning.

[BibT_eX]

[DOI]

Ming Yin

Yu Bai

Yu-Xiang Wang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning.

[BibT_eX]

[DOI]

Ming Yin

Yu Bai

Yu-Xiang Wang

CoRR, 2020

Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning.

[BibT_eX]

[DOI]

Ming Yin

Yu-Xiang Wang

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Ming Yin

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