A review of applications in federated learning

Li, Li, Fan, Yuxi, Tse, Mike ORCID: https://orcid.org/0000-0001-6174-0326 and Lin, Kuo-Yi 2020. A review of applications in federated learning. Computers and Industrial Engineering 149 , 106854. 10.1016/j.cie.2020.106854

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Abstract

Federated Learning (FL) is a collaboratively decentralized privacy-preserving technology to overcome challenges of data silos and data sensibility. Exactly what research is carrying the research momentum forward is a question of interest to research communities as well as industrial engineering. This study reviews FL and explores the main evolution path for issues exist in FL development process to advance the understanding of FL. This study aims to review prevailing application in industrial engineering to guide for the future landing application. This study also identifies six research fronts to address FL literature and help advance our understanding of FL for future optimization. This study contributes to conclude application in industrial engineering and computer science and summarize a review of applications in FL.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Publisher:	Elsevier
ISSN:	0360-8352
Date of First Compliant Deposit:	21 September 2020
Date of Acceptance:	15 September 2020
Last Modified:	06 Dec 2024 00:45
URI:	https://orca.cardiff.ac.uk/id/eprint/134968

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