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Towards Fair Federated Learning
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Towards Fair Federated Learning

Abstract

Federated learning has become increasingly popular as it facilitates collaborative training of machine learning models among multiple clients while preserving their data privacy. In practice, one major challenge for federated learning is to achieve fairness in collaboration among the participating clients, because different clients' contributions to a model are usually far from equal due to various reasons. Besides, as machine learning models …

Authors

Zhou Z; Chu L; Liu C; Wang L; Pei J; Zhang Y

Pagination

pp. 4100-4101

Publisher

Association for Computing Machinery (ACM)

Publication Date

August 14, 2021

DOI

10.1145/3447548.3470814

Name of conference

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining