Convergence Properties of Message-Passing Algorithm for Distributed Convex Optimisation With Scaled Diagonal Dominance

This paper studies the convergence properties of the well-known message-passing algorithm for convex optimisation. Under the assumption of pairwise separability and scaled diagonal dominance, asymptotic convergence is established and a simple bound for the convergence rate is provided for message-pa...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 69; pp. 3868 - 3877
Main Authors: Zhang, Zhaorong, Fu, Minyue
Format: Journal Article
Language:English
Published: New York IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Automobile customizing
Belief propagation
Convergence
convex optimisation
Couplings
Distributed optimisation
Linear programming
Message passing
min-sum algorithm
Optimization
Signal processing algorithms
Task analysis
Telematics
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Summary:This paper studies the convergence properties of the well-known message-passing algorithm for convex optimisation. Under the assumption of pairwise separability and scaled diagonal dominance, asymptotic convergence is established and a simple bound for the convergence rate is provided for message-passing. In comparison with previous results, our results do not require the given convex program to have known convex pairwise components and that our bound for the convergence rate is tighter and simpler. When specialised to quadratic optimisation, we generalise known results by providing a very simple bound for the convergence rate.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2021.3092352