A Survey of Incentive Mechanism Design for Federated Learning

Federated learning is promising in enabling large-scale machine learning by massive clients without exposing their raw data. It can not only enable the clients to preserve the privacy information, but also achieve high learning performance. Existing works of federated learning mainly focus on improv...

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Bibliographic Details
Published in:	IEEE transactions on emerging topics in computing Vol. 10; no. 2; pp. 1035 - 1044
Main Authors:	Zhan, Yufeng, Zhang, Jie, Hong, Zicong, Wu, Leijie, Li, Peng, Guo, Song
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Clients Cloud computing Cognitive tasks Collaborative work Completion time Computational modeling Data models Federated learning incentive mechanism Machine learning Model accuracy Servers Smart grid survey Task analysis Taxonomy Training Training evaluation
ISSN:	2168-6750, 2168-6750
Online Access:	Get full text
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