3 papers
math.OC2026
High-Probability Convergence Theory for Distributed Composite Optimization with Sub-Weibull Noises
Zhan Yu, Zhongjie Shi, Deming Yuan
With the rapid development of distributed optimization (DO) theory, the distributed stochastic gradient methods (DSGMs) occupy an important position. Although the theory of differe…
math.OC2025
Generic Frameworks for Distributed Functional Optimization and Learning over Time-Varying Networks
Zhan Yu, Zhongjie Shi, Deming Yuan +1
In this paper, we establish a distributed functional optimization (DFO) theory over time-varying networks. The vast majority of existing distributed optimization theories are devel…
math.OC2025
Distributed Stochastic Optimization under Heavy-Tailed Noise: A Federated Mirror Descent Approach with High Probability Convergence
Zhan Yu, Lan Liao, Deming Yuan +2
We study the distributed stochastic optimization (DSO) problem under a heavy-tailed noise condition by utilizing a multi-agent system. Despite the extensive research on DSO algorit…