Client Selection in Federated Learning under Imperfections in Environment
Federated learning promises an elegant solution for learning global models across distributed and privacy-protected datasets. However, challenges related to skewed data distribution, limited computational and communication resources, data poisoning, and free riding clients affect the performance of...
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| Główni autorzy: | , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
MDPI AG
2022-02-01
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| Seria: | AI |
| Hasła przedmiotowe: | |
| Dostęp online: | https://www.mdpi.com/2673-2688/3/1/8 |
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