Towards Efficient Hierarchical Federated Learning Design Over Multi-Hop Wireless Communications Networks

Federated learning (FL) has recently received considerable attention and is becoming a popular machine learning (ML) framework that allows clients to train machine learning models in a decentralized fashion without sharing any private dataset. In the FL framework, data for learning tasks are acquire...

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Veröffentlicht in:	IEEE access 2022, p.1-1
Hauptverfasser:	Nguyen, Tu Viet, Ho, Nhan Duc, Hoang, Hieu Thien, Do, Cuong Danh, Wong, Kok-Seng
Format:	Artikel
Sprache:	eng
Schlagworte:	Bandwidth Optimization Communication-Efficiency Computational modeling Data models Distributed Machine Learning Federated learning Multi-Hop Wireless Networks Optimization Servers Task analysis Training
Online-Zugang:	Volltext
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