AUCTION: Automated and Quality-Aware Client Selection Framework for Efficient Federated Learning

The emergency of federated learning (FL) enables distributed data owners to collaboratively build a global model without sharing their raw data, which creates a new business chance for building data market. However, in practical FL scenarios, the hardware conditions and data resources of the partici...

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Bibliographic Details
Published in:	IEEE transactions on parallel and distributed systems Vol. 33; no. 8; pp. 1996 - 2009
Main Authors:	Deng, Yongheng, Lyu, Feng, Ren, Ju, Wu, Huaqing, Zhou, Yuezhi, Zhang, Yaoxue, Shen, Xuemin
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Budgets client selection Clients Coders Collaborative work Data integrity Data models Data privacy data quality Design factors Distributed databases distributed system Encoders-Decoders Federated learning Machine learning Neural networks reinforcement learning Task analysis Training
ISSN:	1045-9219, 1558-2183
Online Access:	Get full text
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