Privacy-Preserving Personalized Federated Learning (PPP-FL) for Medical Imaging

arXiv:2610.27470v1 Announce Type: new Abstract: Federated learning (FL) is a distributed machine learning paradigm that reduces transmission costs, mitigates cross-border data sharing restrictions, and enhances privacy by keeping raw data on local devices. Clients in FL systems train local models and share only updates, which are aggregated by a central server. While this setup limits direct data exposure, FL remains vulnerable to privacy attacks.

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