Publications

Preprints

• Symmetric Rank-k Methods.
  Chengchang Liu, Cheng Chen, Luo Luo.
  arXiv preprint:2303.16188, 2023.

Conference Publications

• Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination.
  Ming Hu, Zhihao Yue, Xiaofei Xie, Cheng Chen, Yihao Huang, Xian Wei, Xiang Lian, Yang Liu, Mingsong Chen.
  Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD Research Track), 2024.
  

• Approximate Matrix Multiplication over Sliding Windows.
  Ziqi Yao*, Lianzhi Li*, Mingsong Chen, Xian Wei, Cheng Chen#.
  Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD Research Track), 2024.
  

• Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization.
  Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low.
  The 41st International Conference on Machine Learning (ICML), 2024. Oral
  

• Robustness Verification of Deep Reinforcement Learning Based Control Systems using Reward Martingales.
  Dapeng Zhi, Peixin Wang, Cheng Chen, Min Zhang.
  The 38th AAAI Conference on Artificial Intelligence (AAAI), 2024.
  

• Block Broyden's Methods for Solving Nonlinear Equations.
  Chengchang Liu, Cheng Chen#, Luo Luo, John C.S. Lui.
  The 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
  

• Boosting Verification of Deep Reinforcement Learning via Piece-Wise Linear Decision Neural Networks.
  Jiaxu Tian, Dapeng Zhi, Si Liu, Peixin Wang, Cheng Chen, Min Zhang.
  The 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
  

• Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization.
  Luo Luo, Yujun Li, Cheng Chen#.
  The 36th Conference on Neural Information Processing Systems (NeurIPS), 2022.
  

• Online Active Regression.
  Cheng Chen*, Yi Li*, Yiming Sun*.
  The 39th International Conference on Machine Learning (ICML), 2022. Long Talk
  

• Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model.
  Cheng Chen, Canzhe Zhao, Shuai Li.
  The 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.

• Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices.
  Luo Luo, Cheng Chen#, Guangzeng Xie, Haishan Ye.
  The 35th AAAI Conference on Artificial Intelligence (AAAI), 2021.
  

• Efficient Projection-Free Algorithms for Saddle Point Problems.
  Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu.
  The 34th Conference on Neural Information Processing Systems (NeurIPS), 2020.
  

• Efficient and Robust High-Dimensional Linear Contextual Bandits.
  Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu, Yijiang Lian.
  The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  

• Efficient Spectrum-Revealing CUR Matrix Decomposition.
  Cheng Chen, Ming Gu, Zhihua Zhang, Weinan Zhang, Yong Yu.
  The 23th International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
  

Journal Papers

• Efficient Policy Evaluation by Matrix Sketching.
  Cheng Chen, Weinan Zhang, Yong Yu.
  Frontiers of Computer Science. 16.5 (2022): 1-9.

• Robust Frequent Directions with Application in Online Learning.
  Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang.
  Journal of Machine Learning Research. 20: 45:1-45:41 (2019).
  

• Fast Fisher discriminant analysis with randomized algorithms.
  Haishan Ye, Yujun Li, Cheng Chen, Zhihua Zhang.
  Pattern Recognition. 72: 82-92 (2017).
  

• Multicategory large margin classification methods: Hinge losses vs. coherence functions.
  Zhihua Zhang, Cheng Chen, Guang Dai, Wu-Jun Li, Dit-Yan Yeung.
  Artificial Intelligence. 215: 55-78 (2014).