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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Vydáno v:Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop s. 1 - 5
Hlavní autoři: Mafakheri, Behnam, Manton, Jonathan H., Shames, Iman
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 08.07.2024
Témata:
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
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Shrnutí: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