6 papers
Distributed Seeking for Fixed Points of Biased Stochastic Operators: A Communication-Efficient Approach
Fan Li, Lei Xu, Xinlei Yi +3
This paper investigates the distributed fixed point seeking problem of sum-separable stochastic operators over the multi-agent network. Based on inexact Krasnosel'ski\uı--Mann ite…
Adaptive Polyak Stepsize with Level-value Adjustment for Distributed Optimization
Chen Ouyang, Yongyang Xiong, Jinming Xu +2
Stepsize selection remains a critical challenge in the practical implementation of distributed optimization. Existing distributed algorithms often rely on restrictive prior knowled…
Loopless Proximal Riemannian Gradient EXTRA for Distributed Optimization on Compact Manifolds
Yongyang Xiong, Chen Ouyang, Keyou You +2
Distributed optimization has gained substantial interest in recent years due to its wide applications in machine learning. However, most of existing algorithms are designed for Euc…
Heterogeneous Stochastic Momentum ADMM for Distributed Nonconvex Composite Optimization
Yangming Zhang, Yongyang Xiong, Jinming Xu +2
This paper investigates the distributed stochastic nonconvex and nonsmooth composite optimization problem. Existing stochastic typically rely on uniform step size strictly bounded…
Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
Pu Qiu, Chen Ouyang, Yongyang Xiong +3
Federated Composite Optimization (FCO) has emerged as a promising framework for training models with structural constraints (e.g., sparsity) in distributed edge networks. However,…
Compressed Gradient Tracking Algorithms for Distributed Nonconvex Optimization
Lei Xu, Xinlei Yi, Guanghui Wen +3
In this paper, we study the distributed nonconvex optimization problem, which aims to minimize the average value of the local nonconvex cost functions using local information excha…