Innovation compression for communication-efficient distributed optimization with linear convergence

Innovation compression for communication-efficient distributed optimization with linear convergence

Information compression is essential to reduce communication cost in distributed optimization over peer-to-peer networks. This paper proposes a communication-efficient linearly convergent distributed (COLD) algorithm to solve strongly convex optimization problems. By compressing innovation vectors,...

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Bibliographic Details
Main Authors: Zhang, Jiaqi, You, Keyou, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Electrical and electronic engineering
Distributed Optimization
Linear Convergence
Online Access:https://hdl.handle.net/10356/170700

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