A Decentralised Asynchronous Optimisation Algorithm with an Application to Phase Retrieval

This paper tackles the challenge of decentralised, nonconvex optimisation in situations where agents work asynchronously. Our main contribution is a new algorithm, partially asynchronous ADMM, designed to solve decentralised optimisation problems like phase retrieval. Importantly, it does not requir...

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Bibliographic Details
Published in:Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop pp. 1 - 5
Main Authors: Mafakheri, Behnam, Manton, Jonathan H., Shames, Iman
Format: Conference Proceeding
Language:English
Published: IEEE 08.07.2024
Subjects:
Alternating Direction Method of Multipliers
Array signal processing
Asynchronous Distributed Optimisation
Conferences
Douglas-Rachford Splitting
Optimization
Performance analysis
Phase Retrieval
Sensor arrays
Signal processing algorithms
ISSN:2151-870X
Online Access:Get full text
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Summary:This paper tackles the challenge of decentralised, nonconvex optimisation in situations where agents work asynchronously. Our main contribution is a new algorithm, partially asynchronous ADMM, designed to solve decentralised optimisation problems like phase retrieval. Importantly, it does not require a central coordinator and can work with arbitrary connected network setups. We also prove that our algorithm is equivalent to the randomised block coordinate Douglas-Rachford Splitting method. To illustrate the algorithm's effectiveness, we provide numerical results for the distributed phase retrieval problem, demonstrating its correctness and performance.
ISSN:2151-870X
DOI:10.1109/SAM60225.2024.10636375