Federated Learning with Extremely Noisy Clients via Negative
Distillation

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Federated Learning with Extremely Noisy Clients via Negative Distillation

20 December 2023

Bo Han

Yiu-ming Cheung

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Papers citing "Federated Learning with Extremely Noisy Clients via Negative Distillation"

4 / 4 papers shown

Title
FNBench: Benchmarking Robust Federated Learning against Noisy Labels Xuefeng Jiang Jia Li Nannan Wu Z. F. Wu Xujing Li Sheng Sun Gang Xu Yansen Wang Qi Li Min Liu FedML 87 3 0 10 May 2025
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels Yuxin Tian Mouxing Yang Yuhao Zhou Jian Wang Qing Ye Tongliang Liu Gang Niu Jiancheng Lv FedML 148 0 0 30 Nov 2024
FedNoisy: Federated Noisy Label Learning Benchmark Siqi Liang Jintao Huang Junyuan Hong Dun Zeng Jiayu Zhou Zenglin Xu FedML 151 7 0 20 Jun 2023
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 159 78 0 25 Feb 2021

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