Reliable Federated Learning for Mobile Networks

Federated learning, as a promising machine learning approach, has emerged to leverage a distributed personalized dataset from a number of nodes, for example, mobile devices, to improve performance while simultaneously providing privacy preservation for mobile users. In federated learning, training d...

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Bibliographic Details
Published in:	IEEE wireless communications Vol. 27; no. 2; pp. 72 - 80
Main Authors:	Kang, Jiawen, Xiong, Zehui, Niyato, Dusit, Zou, Yuze, Zhang, Yang, Guizani, Mohsen
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Cognitive tasks Consortia Cryptography Data models Data privacy Electronic devices Federated learning Iterative methods Machine learning Metasearch Mobile handsets Network reliability Numerical analysis Performance enhancement Public relations Reliability analysis Reputation management Task analysis Training data Wireless networks Workers
ISSN:	1536-1284, 1558-0687
Online Access:	Get full text
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