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20232026
most citedTackling Noisy Clients in Federated Learning with End-to-end Label Correction

27 citations · 36 across the 21 of their papers we have counts for

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cs.CV2025

FNBench: Benchmarking Robust Federated Learning against Noisy Labels

Xuefeng Jiang, Jia Li, Nannan Wu +7

Robustness to label noise within data is a significant challenge in federated learning (FL). From the data-centric perspective, the data quality of distributed datasets can not be…