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

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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Bibliographic Details
Main Authors:	Maria Raftopoulou, Jose Mairton B. da Silva, Remco Litjens, H. Vincent Poor, Piet van Mieghem
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Series:	IEEE Transactions on Machine Learning in Communications and Networking
Subjects:	Agent selection federated learning machine learning wireless networks
Online Access:	https://ieeexplore.ieee.org/document/10654373/
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