Shi Pu’s Homepage

Welcome! I am an assistant professor in the School of Data Science at The Chinese University of Hong Kong, Shenzhen.

Research Interests

Distributed optimization, machine learning, multi-agent networks.

See here for our research topics, and here for our publications.

Openings

We are always looking for self-motivated students with solid mathematical background and research interests in optimization, machine learning, distributed algorithms, game theory, etc.

Recent News

• March. 2025: Our paper, Distributed Random Reshuffling Methods with Improved Convergence (with Kun Huang and Linli Zhou), has been accepted for publication in IEEE Transactions on Automatic Control!
• February. 2025: Our paper, An Accelerated Distributed Stochastic Gradient Method with Momentum (with Kun Huang and Angelia Nedić), has been accepted for publication in Mathematical Programming!
• February. 2025: I gave a talk titled “B-ary Tree Push-Pull Method for Distributed Optimization” at Anhui University. Thank Prof. Songsong Cheng for inviting!
• December. 2024: Congratulations to Kun Huang for passing the PhD defense!
• December. 2024: Our paper, Distributed Normal Map-based Stochastic Proximal Gradient Methods over Networks (with Kun Huang and Angelia Nedić), is online!
• December. 2024: Our paper, Linear Convergence Analysis of Single-loop Algorithm for Bilevel Optimization via Small-gain Theorem (with Jianhui Li, Jianqi Chen and Junfeng Wu), is online!
• November. 2024: I gave a talk titled “B-ary Tree Push-Pull Method for Distributed Optimization” at SUSTech. Thank Prof. Jin Zhang for inviting!
• September. 2024: Our paper, CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence (with Kun Huang), has been accepted for publication in IEEE Transactions on Automatic Control as Full Paper!
• September. 2024: Our paper, B-ary Tree Push-Pull Method is Provably Efficient for Decentralized Learning on Heterogeneous Data (with Runze You), has been accepted by NeurIPS 2024!
• August. 2024: Our paper, A Robust Compressed Push-Pull Method for Decentralized Nonconvex Optimization (with Yiwei Liao, Zhuorui Li and Tsung-Hui Chang), is online!
• April. 2024: Our paper, Distributed Stochastic Optimization under a General Variance Condition (with Kun Huang and Xiao Li), has been accepted for publication in IEEE Transactions on Automatic Control as Full Paper!
• April. 2024: Our paper, B-ary Tree Push-Pull Method is Provably Efficient for Decentralized Learning on Heterogeneous Data (with Runze You), is online!
• February. 2024: Our paper, An Accelerated Distributed Stochastic Gradient Method with Momentum (with Kun Huang and Angelia Nedić), is online!
• December. 2023: Our paper, Provably Accelerated Decentralized Gradient Method Over Unbalanced Directed Graphs (with Zhuoqing Song, Lei Shi and Ming Yan) has been accepted for publication in SIAM Journal on Optimization!
• August. 2023: I became an IEEE senior member.
• August. 2023: I gave a talk titled “Distributed Stochastic Gradient Methods over Networks” during The 14th International Conference on Numerical Optimization and Numerical Linear Algebra.
• July. 2023: Our paper, A Linearly Convergent Robust Compressed Push-Pull Method for Decentralized Optimization (with Yiwei Liao and Zhuorui Li), has been accepted by 2023 IEEE Conference on Decision and Control!
• Jun. 2023: Our new paper, Distributed Random Reshuffling Methods with Improved Convergence (with Linli Zhou and Kun Huang), is online!
• Jun. 2023: Our paper, Optimal Gradient Tracking for Decentralized Optimization (with Zhuoqing Song, Lei Shi and Ming Yan) has been accepted for publication in Mathematical Programming!
• May. 2023: I gave an invited talk titled “Asymptotic Network Independence in Distributed Stochastic Gradient Methods” during MOS2023. Thank Prof. Xiangfeng Wang, Prof. Hongjin He and Prof. Wenxing Zhang for organizing!
• Mar. 2023: Our paper, A Linearly Convergent Robust Compressed Push-Pull Method for Decentralized Optimization (with Yiwei Liao and Zhuorui Li), is online!
• Mar. 2023: Our paper, Distributed Random Reshuffling over Networks (with Kun Huang, Xiao Li, Andre Milzarek, and Junwen Qiu), has been accepted for publication in IEEE Transactions on Signal Processing!
• Jan. 2023: Our paper, Distributed Stochastic Optimization under a General Variance Condition (with Kun Huang and Xiao Li), is online!
• Jan. 2023: Our paper, CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence (with Kun Huang), is online!