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A review of applications in federated learning - 2020

Research Area:  Machine Learning

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.

Author(s) Name:  Li Li, Yuxi Fan, MikeTse, Kuo-YiLin

Journal name:  Computers & Industrial Engineering

Conferrence name:  

Publisher name:  ELSEVIER

DOI:  https://doi.org/10.1016/j.cie.2020.106854

Volume Information:  Volume 149, November 2020, 106854