Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory

• Main Authors: Masuyama, Naoki, Nojima, Yusuke, Toda, Yuichiro, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki
• Format: Article
• Published: Institute of Electrical and Electronics Engineers 2024
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.um.edu.my/47098/; https://doi.org/10.1109/ACCESS.2024.3467114

With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. In the clustering domain, various algorithms with a federated learning framework (i.e., federated clustering) have been actively studied and showed high clustering perfo...