Publications

Preprints

1. Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation
   Minshuo Chen, Wenjing Liao, Hongyuan Zha, and Tuo Zhao

Journal Papers

1. Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks: Function Approximation and Statistical Recovery
   Minshuo Chen, Haoming Jiang, Wenjing Liao, and Tuo Zhao
   IMA Information and Inference, to appear
2. Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks
   Minshuo Chen, Hao Liu, Wenjing Liao, and Tuo Zhao
   Submitted to Operations Research, under revision

Conference Papers

1. Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
   Yuqing Wang, Minshuo Chen, Tuo Zhao, and Molei Tao
   International Conference on Learning Representations (ICLR), 2022
2. Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL
   Minshuo Chen, Yan Li, Zhuoran Yang, Zhaoran Wang, and Tuo Zhao
   Annual Conference on Neural Information Processing Systems (NeurIPS), 2021
3. How Important is the Train-Validation Split in Meta-Learning?
   Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham Kakade, Huan Wang, and Caiming Xiong
   International Conference on Machine Learning (ICML), 2021
4. Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
   Hao Liu, Minshuo Chen, Tuo Zhao, and Wenjing Liao
   International Conference on Machine Learning (ICML), 2021
5. Towards Understanding Hierarchical Learning: Benefits of Neural Representations
   Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, and Richard Socher
   Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
6. Differentiable Top-k Operator with Optimal Transport
   Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, and Tomas Pfister
   Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
7. On Generalization Bounds of a Family of Recurrent Neural Networks
   Minshuo Chen, Xingguo Li, and Tuo Zhao
   International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
8. Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers
   David Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga S. Mannem, Tuo Zhao, and Hua Wang
   IEEE Radio Frequency Integrated Circuits Symposium (RFIC), 2020
9. On Computation and Generalization of Generative Adversarial Imitation Learning
   Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, and Tuo Zhao
   International Conference on Learning Representations (ICLR), 2020
10. Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
    Minshuo Chen, Haoming Jiang, Wenjing Liao, and Tuo Zhao (Alphabetical Order)
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2019
11. Towards Understanding the Importance of Shortcut Connections in Residual Networks
    Tianyi Liu*, Minshuo Chen*, Mo Zhou, Simon Du, Enlu Zhou, and Tuo Zhao (* Equal Contribution)
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2019
12. On Scalable and Efficient Computation of Large Scale Optimal Transport
    Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, and Hongyuan Zha
    International Conference on Machine Learning (ICML), 2019
13. On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
    Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, and Tuo Zhao
    International Conference on Learning Representations (ICLR), 2019
14. Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization
    Minshuo Chen, Lin Yang, Mengdi Wang, and Tuo Zhao
    Annual Conference on Neural Information Processing Systems (NeurIPS), 2018