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20242026
most citedAchieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

cs.LG20261 cited

Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization

Luyao Guo, Sulaiman A. Alghunaim, Kun Yuan +2

The ProxSkip algorithm for distributed optimization is gaining increasing attention due to its effectiveness in reducing communication. However, existing analyses of ProxSkip are l…

math.OC2026

Local adapt-then-combine algorithms for distributed nonsmooth optimization: Achieving provable communication acceleration

Luyao Guo, Xinli Shi, Wenying Xu +1

This paper is concerned with the distributed composite optimization problem over networks, where agents aim to minimize a sum of local smooth components and a common nonsmooth term…

math.OC2026

Perturbed Proximal Gradient ADMM for Nonconvex Composite Optimization

Yuan Zhou, Xinli Shi, Luyao Guo +2

This paper proposes a Perturbed Proximal Gradient ADMM (PPG-ADMM) framework for solving general nonconvex composite optimization problems, where the objective function consists of…

math.OC2025

A Proximal Gradient Method With Probabilistic Multi-Gossip Communications for Decentralized Composite Optimization

Luyao Guo, Luqing Wang, Xinli Shi +1

Decentralized optimization methods with local updates have recently gained attention for their provable ability to communication acceleration. In these methods, nodes perform sever…

math.OC2024

Differentially Private Decentralized Optimization with Relay Communication

Luqing Wang, Luyao Guo, Shaofu Yang +1

Security concerns in large-scale networked environments are becoming increasingly critical. To further improve the algorithm security from the design perspective of decentralized o…