Robust Federated Fuzzy C-Means Algorithm in Heterogeneous Scenarios

The federated fuzzy C-means (federated FCM) extends the traditional Fuzzy C-means (FCM) to the federated learning (FL) scenario, aiming to address the data privacy preservation issue of soft clustering in distributed environments. However, a significant challenge persists with existing federated FCM...

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Vydané v:	IEEE transactions on fuzzy systems Ročník 33; číslo 9; s. 3168 - 3181
Hlavní autori:	Zhang, Qixian, Deng, Zhaohong, Zhang, Wei, Zhao, Zhuangzhuang, Xiao, Zhiyong, Choi, Kup-Sze, Wang, Guanjin, Ge, Yuxi, Hu, Shudong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.09.2025
Predmet:	Approximation algorithms Clustering algorithms Clustering methods Computational modeling Convergence Distributed databases Electronic mail Federated clustering (FC) federated learning (FL) fuzzy clustering Fuzzy logic heterogeneity Optimization robustness Servers
ISSN:	1063-6706, 1941-0034
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