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Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning
Feb. 8, 2024, 5:10 a.m. | Meiying Zhang Huan Zhao Sheldon Ebron Kan Yang
cs.CR updates on arXiv.org arxiv.org
can client clients compensation cs.ai cs.cr cs.dc cs.lg data distributed divergent evaluation fair federated federated learning noisy non performance risk updates
More from arxiv.org / cs.CR updates on arXiv.org
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