FedNoisy: Federated Noisy Label Learning Benchmark

20 June 2023

Papers citing "FedNoisy: Federated Noisy Label Learning Benchmark"

7 / 7 papers shown

Title
Federated Learning Client Pruning for Noisy Labels Mahdi Morafah Hojin Chang C. L. P. Chen Bill Lin 30 0 0 11 Nov 2024
Federated Learning with Extremely Noisy Clients via Negative Distillation Yang Lu Lin Chen Yonggang Zhang Yiliang Zhang Bo Han Yiu-ming Cheung Hanzi Wang FedML 15 8 0 20 Dec 2023
Advocating for the Silent: Enhancing Federated Generalization for Non-Participating Clients Zheshun Wu Zenglin Xu Dun Zeng Qifan Wang Jie Liu FedML 17 1 0 11 Oct 2023
Understanding Adversarial Transferability in Federated Learning Yijiang Li Ying Gao Haohan Wang AAML FedML 9 1 0 01 Oct 2023
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels Zhuowei Wang Tianyi Zhou Guodong Long Bo Han Jing Jiang FedML 16 11 0 20 May 2022
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 85 936 0 03 Feb 2021
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 156 553 0 27 Jul 2020