Exact Diffusion for Distributed Optimization and Learning—Part I: Algorithm Development

DOI10.1109/TSP.2018.2875898zbMath1414.90277arXiv1702.05122OpenAlexW2964165783MaRDI QIDQ4628229

Bicheng Ying, Ali H. Sayed, Kun Yuan, Xiaochuan Zhao

Publication date: 6 March 2019

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.05122

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Convex programming (90C25) Stochastic programming (90C15) Deterministic network models in operations research (90B10)

Related Items (8)

Linear convergence of primal-dual gradient methods and their performance in distributed optimization ⋮ Correction-based diffusion LMS algorithms for distributed estimation ⋮ Linear convergence rate analysis of a class of exact first-order distributed methods for weight-balanced time-varying networks and uncoordinated step sizes ⋮ Golden ratio proximal gradient ADMM for distributed composite convex optimization ⋮ Proximal nested primal-dual gradient algorithms for distributed constraint-coupled composite optimization ⋮ On the linear convergence of two decentralized algorithms ⋮ Unnamed Item ⋮ On the convergence of exact distributed generalisation and acceleration algorithm for convex optimisation

This page was built for publication: Exact Diffusion for Distributed Optimization and Learning—Part I: Algorithm Development