Minshuo Chen
Orcid: 0000-0001-6344-845X
According to our database1,
Minshuo Chen
authored at least 52 papers
between 2018 and 2024.
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Bibliography
2024
Efficient Reinforcement Learning With Impaired Observability: Learning to Act With Delayed and Missing State Observations.
IEEE Trans. Inf. Theory, October, 2024
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds.
J. Mach. Learn. Res., 2024
J. Mach. Learn. Res., 2024
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data.
CoRR, 2024
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization.
CoRR, 2024
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory.
CoRR, 2024
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Sample Complexity of Preference-Based Nonparametric Off-Policy Evaluation with Deep Networks.
CoRR, 2023
Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems.
CoRR, 2023
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks.
CoRR, 2023
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Design and Analysis of a Field Modulated Transverse Flux Linear Generator Used in Direct Drive Wave Energy Converter.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories.
Proceedings of the International Conference on Machine Learning, 2023
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Representation and statistical properties of deep neural networks on structured data.
PhD thesis, 2022
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization.
CoRR, 2022
CoRR, 2022
Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network.
CoRR, 2022
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the IECON 2022, 2022
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
A Stator-PM Transverse Flux Permanent Magnet Linear Generator for Direct Drive Wave Energy Converter.
IEEE Access, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
2020
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks.
CoRR, 2020
Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers.
CoRR, 2020
Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control.
Proceedings of the 7th International Conference on Learning Representations, 2019
2018
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018