Asynchronous consensus for multi-agent systems and its application to Federated Learning

Author:

Carrascosa CarlosORCID,Pico AaronORCID,Matagne Miro-Manuel,Rebollo MiguelORCID,Rincon J.A.ORCID

Funder

Euskal Herriko Unibertsitatea

Ministerio de Ciencia e Innovación

European Regional Development Fund

Agencia Estatal de Investigación

Publisher

Elsevier BV

Reference32 articles.

1. An ensemble of echo state networks for predicting the energy production of wind plants;Al-Dahidi,2020

2. Consensus in multi-agent systems: a review;Amirkhani;Artif. Intell. Rev.,2022

3. Open challenges in federated machine learning;Baresi;IEEE Internet Comput.,2023

4. Practical secure aggregation for privacy-preserving machine learning;Bonawitz,2017

5. Co-learning: Consensus-based learning for multi-agent systems;Carrascosa,2022

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