Asynchronous message-passing and zeroth-order optimization based distributed learning with a use-case in resource allocation in communication networks

Distributed learning and adaptation have received significant interest and found wide-ranging applications in machine learning and signal processing. While various approaches, such as shared-memory optimization, multi-task learning, and consensus-based learning (e.g., federated learning and learning...

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Veröffentlicht in:	Ieee Transactions On Signal And Information Processing Over Networks 2024-11, Vol.10, p.916-931
Hauptverfasser:	Behmandpoor, Pourya, Moonen, marc, Patrinos, Panos
Format:	Artikel
Sprache:	eng
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