Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications

Fuente: arXiv

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Bibliographic Details
Main Authors:	Cremonesi, Francesco, Vesin, Marc, Cansiz, Sergen, Bouillard, Yannick, Balelli, Irene, Innocenti, Lucia, Silva, Santiago, Ayed, Samy-Safwan, Taiello, Riccardo, Kameni, Laetita, Vidal, Richard, Orlhac, Fanny, Nioche, Christophe, Lapel, Nathan, Houis, Bastien, Modzelewski, Romain, Humbert, Olivier, Önen, Melek, Lorenzi, Marco
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2304.12012