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Privacy-Preserving U-Shaped Split Federated Learning for Space–Air–Ground–Sea Integrated Networks

Federated learning enables privacy-preserving distributed intelligence but faces challenges in balancing computation, communication, and privacy in heterogeneous networks. To address these issues, this paper proposes a privacy-preserving U-shaped split federated learning (USFL) framework for space–a...

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Detalhes bibliográficos
Principais autores:	Xin Sun, Tingting Yang, Xiufeng Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Mathematics
Assuntos:	federated learning split learning privacy-preserving learning differential privacy edge intelligence resource-constrained networks
Acesso em linha:	https://www.mdpi.com/2227-7390/14/8/1357
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Privacy-Preserving U-Shaped Split Federated Learning for Space–Air–Ground–Sea Integrated Networks

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