FedMSA: A Model Selection and Adaptation System for Federated Learning

Federated Learning (FL) enables multiple clients to train a shared model collaboratively without sharing any personal data. However, selecting a model and adapting it quickly to meet user expectations in a large-scale FL application with heterogeneous devices is challenging. In this paper, we propos...

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Detalles Bibliográficos
Autores principales: Sun, Rui, Li, Yinhao, Shah, Tejal, Sham, Ringo W. H., Szydlo, Tomasz, Qian, Bin, Thakker, Dhaval, Ranjan, Rajiv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571508/
https://www.ncbi.nlm.nih.gov/pubmed/36236343
http://dx.doi.org/10.3390/s22197244

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571508/
https://www.ncbi.nlm.nih.gov/pubmed/36236343
http://dx.doi.org/10.3390/s22197244

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