Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning

Fuente: arXiv

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Bibliographic Details
Main Authors:	Zhang, Meiying, Zhao, Huan, Ebron, Sheldon, Yang, Kan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2402.04409