陈程 - 华东师范大学 - 软件工程学院

个人简介

陈程，华东师范大学软件工程学院副教授。于上海交通大学计算机科学与技术专业本科直博，博士期间在美国加州大学伯克利分校数学系公派联培一年，之后前往新加坡南洋理工大学数学系从事博士后研究工作。主要研究方向包括在线机器学习、最优化、强化学习以及矩阵近似，已在机器学习领域的顶级会议和期刊上发表学术论文十余篇，并获得国家自然科学基金青年科学基金项目资助。目前担任机器学习旗舰期刊JMLR的编委会审稿人 (Editorial board reviewer)，并多次担任NeurIPS、ICML、ICLR等机器学习顶级会议的审稿人。教育经历 2013.9.-2021.3. 上海交通大学博士 2016.9.-2017.10. 加州大学伯克利分校公派联培博士 2009.9.-2013.6. 上海交通大学本科工作经历 2023.4.-至今华东师范大学副教授 2021.9.-2023.1. 南洋理工大学博士后

研究领域

我的研究目标是设计高效、鲁棒且有理论保证的机器学习算法，主要研究方向包括：在线学习（Online Learning）强化学习（Reinforcement Learning）联邦学习（Federated Learning）最优化方法（Optimization Methods）矩阵近似（Matrix Approximation）

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

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. (To appear) 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. (To appear) 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 (To appear) 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. (To appear) 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).

学术兼职

国际会议审稿人： ICML 2021-2023 NeurIPS 2021-2023 ICLR 2022-2023 IJCAI 2023 期刊审稿人： Journal of Machine Learning Research Transactions on Machine Learning Research Frontiers of Computer Science