Fundamentals of Federated Learning

Choong Seon Hong; Latif U. Khan; Mingzhe Chen; Dawei Chen; Walid Saad; Zhu Han

doi:10.1007/978-981-16-4963-9_2

Fundamentals of Federated Learning

Choong Seon Hong, Latif U. Khan, Mingzhe Chen, Dawei Chen, Walid Saad, Zhu Han

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Abstract

In this chapter, we provide an overview of the fundamentals of FL. First, we discuss a brief history of machine learning. Second, we present the key design challenges for FL over wireless networks. Next, we critically discuss the key design aspects, such as resource allocation, incentive mechanism design, security, and privacy of FL over wireless networks. Finally, we critically discuss existing FL algorithms.

Original language	English
Title of host publication	Wireless Networks (United Kingdom)
Publisher	Springer Science and Business Media B.V.
Pages	11-23
Number of pages	13
DOIs	https://doi.org/10.1007/978-981-16-4963-9_2
Publication status	Published - 2021

Publication series

Name	Wireless Networks (United Kingdom)
ISSN (Print)	2366-1186
ISSN (Electronic)	2366-1445

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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10.1007/978-981-16-4963-9_2

Cite this

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title = "Fundamentals of Federated Learning",

abstract = "In this chapter, we provide an overview of the fundamentals of FL. First, we discuss a brief history of machine learning. Second, we present the key design challenges for FL over wireless networks. Next, we critically discuss the key design aspects, such as resource allocation, incentive mechanism design, security, and privacy of FL over wireless networks. Finally, we critically discuss existing FL algorithms.",

author = "{Seon Hong}, Choong and Khan, {Latif U.} and Mingzhe Chen and Dawei Chen and Walid Saad and Zhu Han",

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Fundamentals of Federated Learning

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