Agent Selection Framework for Federated Learning in Resource-Constrained Wireless Networks

Federated learning is an effective method to train a machine learning model without requiring to aggregate the potentially sensitive data of agents in a central server. However, the limited communication bandwidth, the hardware of the agents and a potential application-specific latency requirement i...

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Veröffentlicht in:	IEEE transactions on machine learning in communications and networking Jg. 2; S. 1265 - 1282
Hauptverfasser:	Raftopoulou, Maria, da Silva, Jose Mairton B., Litjens, Remco, Vincent Poor, H., van Mieghem, Piet
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2024
Schlagworte:	Accuracy Agent selection Computer Science with specialization in Computer Communication Data models Datavetenskap med inriktning mot datorkommunikation Device selection federated learning machine learning Measurement Servers Training Vectors Wireless networks
ISSN:	2831-316X, 2831-316X
Online-Zugang:	Volltext
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