Joint Client Selection and Task Assignment for Multi-Task Federated Learning in MEC Networks

In this paper, we investigate the multi-task federated learning in mobile edge computing (MEC) networks where a central server assigns different federated learning tasks to different MEC servers and select feasible clients to participate in the federated learning training process. The problem is for...

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Bibliographic Details

Published in:	2021 IEEE Global Communications Conference (GLOBECOM) pp. 1 - 6
Main Authors:	Cheng, Zhipeng, Min, Minghui, Liwang, Minghui, Gao, Zhibin, Huang, Lianfen
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2021
Subjects:	Client selection Clustering algorithms Collaborative work MEC multi-task federated learning Multitasking Search problems Simulation task assignment Three-dimensional displays Training
Online Access:	Get full text
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