Chen, Minshuo

43 publications

ICLR 2025 Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data Hengyu Fu, Zehao Dou, Jiawei Guo, Mengdi Wang, Minshuo Chen

NeurIPS 2025 Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification Zeqi Ye, Minshuo Chen

NeurIPS 2025 High-Order Flow Matching: Unified Framework and Sharp Statistical Rates Maojiang Su, Jerry Yao-Chieh Hu, Yi-Chen Lee, Ning Zhu, Jui-Hui Chung, Shang Wu, Zhao Song, Minshuo Chen, Han Liu

ICLR 2025 On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

ICLRW 2025 Statistical Foundations of Conditional Diffusion Transformers Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu

NeurIPS 2024 A Theoretical Perspective for Speculative Decoding Algorithm Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang

JMLR 2024 Deep Nonparametric Estimation of Operators Between Infinite Dimensional Spaces Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao

NeurIPS 2024 Gradient Guidance for Diffusion Models: An Optimization Perspective Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang

NeurIPS 2024 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

AISTATS 2024 Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang

JMLR 2024 Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICLR 2024 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

ICML 2024 Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei

ICML 2024 Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang

ICLR 2023 Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao

NeurIPSW 2023 Counterfactual Generative Models for Time-Varying Treatments Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu

NeurIPSW 2023 Counterfactual Generative Models for Time-Varying Treatments Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu

ICML 2023 Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

NeurIPS 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

ICMLW 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

NeurIPSW 2023 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

NeurIPS 2023 Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang

ICLR 2023 Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds Using Deep Networks Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICMLW 2023 Sample-Efficient Learning of POMDPs with Multiple Observations in Hindsight Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai

ICML 2023 Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang

ICML 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

NeurIPSW 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

ICLR 2022 Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao

NeurIPS 2022 On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao

ICML 2021 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao

ICML 2021 How Important Is the Train-Validation Split in Meta-Learning? Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong

NeurIPS 2021 Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao

NeurIPSW 2020 Differentiable Top-$k$ with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

NeurIPS 2020 Differentiable Top-K with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

ICLR 2020 On Computation and Generalization of Generative Adversarial Imitation Learning Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao

AISTATS 2020 On Generalization Bounds of a Family of Recurrent Neural Networks Minshuo Chen, Xingguo Li, Tuo Zhao

NeurIPS 2020 Towards Understanding Hierarchical Learning: Benefits of Neural Representations Minshuo Chen, Yu Bai, Jason Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher

NeurIPS 2019 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao

ICLR 2019 On Computation and Generalization of Generative Adversarial Networks Under Spectrum Control Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao

ICML 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

ICLRW 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

NeurIPS 2019 Towards Understanding the Importance of Shortcut Connections in Residual Networks Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S Du, Enlu Zhou, Tuo Zhao

NeurIPS 2018 Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao