Distributed Subgradient Method With Random Quantization and Flexible Weights: Convergence Analysis

The distributed subgradient (DSG) method is a widely used algorithm for coping with large-scale distributed optimization problems in machine-learning applications. Most existing works on DSG focus on ideal communication between cooperative agents, where the shared information between agents is exact...

Full description

Bibliographic Details

Published in:	IEEE transactions on cybernetics Vol. 54; no. 2; pp. 1 - 13
Main Authors:	Xia, Zhaoyue, Du, Jun, Jiang, Chunxiao, Poor, H. Vincent, Han, Zhu, Ren, Yong
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.02.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Convergence Convex functions Distributed consensus Distributed databases distributed optimization Linear programming Machine learning multiagent systems nonconvex optimization Optimization Quantization (signal) Upper bounds Wireless communication
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!