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

27 citations · 27 across the 1 of their papers we have counts for

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cs.LG2024★ 27 cited

Tackling Noisy Clients in Federated Learning with End-to-end Label Correction

Xuefeng Jiang, Sheng Sun, Jia Li +6

Recently, federated learning (FL) has achieved wide successes for diverse privacy-sensitive applications without sacrificing the sensitive private information of clients. However,…