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2020 – today
- 2022
[b1]Minshuo Chen:
Representation and statistical properties of deep neural networks on structured data. Georgia Institute of Technology, Atlanta, GA, USA, 2022- [c17]Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao:
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. ICLR 2022 - [c16]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML 2022: 13669-13703 - [c15]Peiwen Tan, Lei Huang, Minshuo Chen, Yang Li, Ruiyang Ma, Jianlong Yang:
Optimal Energy Management Scheme for Wave-HESS DC Microgrid. IECON 2022: 1-6 - [i22]Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao:
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. CoRR abs/2201.00217 (2022) - [i21]Siawpeng Er, Edward Liu, Minshuo Chen, Yan Li, Yuqi Liu, Tuo Zhao, Hua Wang:
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 abs/2201.02141 (2022) - [i20]Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao, Yao Xie:
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. CoRR abs/2205.02043 (2022) - [i19]Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. CoRR abs/2206.02887 (2022) - [i18]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR abs/2206.04569 (2022) - [i17]Jiahui Cheng, Minshuo Chen, Hao Liu, Tuo Zhao, Wenjing Liao:
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. CoRR abs/2212.00700 (2022) - 2021
- [j1]Minshuo Chen
, Lei Huang, Peiwen Tan, Yang Li, Ghulam Ahmad, Minqiang Hu:
A Stator-PM Transverse Flux Permanent Magnet Linear Generator for Direct Drive Wave Energy Converter. IEEE Access 9: 9949-9957 (2021) - [c14]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) 2021: 6524-6538 - [c13]Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong:
How Important is the Train-Validation Split in Meta-Learning? ICML 2021: 543-553 - [c12]Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao:
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. ICML 2021: 6770-6780 - [c11]Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao:
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. NeurIPS 2021: 17913-17926 - [i16]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR abs/2105.12002 (2021) - [i15]Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao:
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. CoRR abs/2109.02832 (2021) - [i14]Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao:
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. CoRR abs/2110.03677 (2021) - 2020
- [c10]Minshuo Chen, Xingguo Li, Tuo Zhao:
On Generalization Bounds of a Family of Recurrent Neural Networks. AISTATS 2020: 1233-1243 - [c9]Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Imitation Learning. ICLR 2020 - [c8]Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher:
Towards Understanding Hierarchical Learning: Benefits of Neural Representations. NeurIPS 2020 - [c7]Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister:
Differentiable Top-k with Optimal Transport. NeurIPS 2020 - [i13]Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Imitation Learning. CoRR abs/2001.02792 (2020) - [i12]Minshuo Chen, Wenjing Liao, Hongyuan Zha, Tuo Zhao:
Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation. CoRR abs/2002.03938 (2020) - [i11]Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister:
Differentiable Top-k Operator with Optimal Transport. CoRR abs/2002.06504 (2020) - [i10]Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher:
Towards Understanding Hierarchical Learning: Benefits of Neural Representations. CoRR abs/2006.13436 (2020) - [i9]David Joseph Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga Sasikanth Mannem, Tuo Zhao, Hua Wang:
Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. CoRR abs/2008.10755 (2020) - [i8]Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong:
How Important is the Train-Validation Split in Meta-Learning? CoRR abs/2010.05843 (2020) - [i7]Minshuo Chen, Hao Liu, Wenjing Liao, Tuo Zhao:
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks. CoRR abs/2011.01797 (2020)
2010 – 2019
- 2019
- [c6]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. ICLR (Poster) 2019 - [c5]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. DGS@ICLR 2019 - [c4]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. ICML 2019: 6882-6892 - [c3]Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao:
Towards Understanding the Importance of Shortcut Connections in Residual Networks. NeurIPS 2019: 7890-7900 - [c2]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. NeurIPS 2019: 8172-8182 - [i6]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. CoRR abs/1905.00158 (2019) - [i5]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. CoRR abs/1908.01842 (2019) - [i4]Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao:
Towards Understanding the Importance of Shortcut Connections in Residual Networks. CoRR abs/1909.04653 (2019) - [i3]Minshuo Chen, Xingguo Li, Tuo Zhao:
On Generalization Bounds of a Family of Recurrent Neural Networks. CoRR abs/1910.12947 (2019) - 2018
- [c1]Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao:
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. NeurIPS 2018: 3500-3510 - [i2]Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao:
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. CoRR abs/1803.02312 (2018) - [i1]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of GANs with Spectrum Control. CoRR abs/1812.10912 (2018)
Coauthor Index
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