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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Vydáno v:	IEEE wireless communications Ročník 27; číslo 2; s. 72 - 80
Hlavní autoři:	Kang, Jiawen, Xiong, Zehui, Niyato, Dusit, Zou, Yuze, Zhang, Yang, Guizani, Mohsen
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
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