Learning Cautiously in Federated Learning with Noisy and Heterogeneous
Clients

Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients

6 April 2023

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Papers citing "Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients"

9 / 9 papers shown

Title
Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data Alpaslan Gokcen Ali Boyaci FedML 79 0 0 14 May 2025
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 91 3 0 10 May 2025
Data Quality Control in Federated Instruction-tuning of Large Language Models Yaxin Du Guangyi Liu Fengting Yuchi W. Zhao Jingjing Qu Yanjie Wang Siheng Chen ALM FedML 129 2 0 15 Oct 2024
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning Boyu Fan Chenrui Wu Xiang Su Pan Hui FedML 108 3 0 06 Jul 2024
Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank Decomposition Xinghao Wu Xuefeng Liu Jianwei Niu Haolin Wang Shaojie Tang Guogang Zhu Hao Su FedML 83 8 0 28 Jun 2024
FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity Zhaobin Sun Nannan Wu Junjie Shi Li Yu Xin Yang Kwang-Ting Cheng Zengqiang Yan 76 0 0 27 Jun 2024
Multi-level Personalized Federated Learning on Heterogeneous and Long-Tailed Data Rongyu Zhang Yun Chen Chenrui Wu Fangxin Wang Boyan Li 86 12 0 10 May 2024
FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions Changjuan Ran Yeting Guo Fang Liu Shenglan Cui Yunfan Ye FedML 110 1 0 25 Apr 2024
FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning Lingzhi Gao Zexi Li Yang Lu Chao Wu 102 7 0 30 Nov 2023