Author

S. Amitrano

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#federated learning Book Open access Nov 2026

Less Federation, More Personalization: One-Shot Multi-View Clustering for Federated Fall Detection

A two-stage framework is proposed in which each client first learns label-free representations using FMMVCC, a multi-view clustering encoder that combines reconstruction, cross-view consistency, contrastive learning, and prototype-based objectives, showing strong representation quality and providing competitive perform...

Donato Cerciello, L. Schiavo, Angel Panizo LLedot et al. · 0 citations

#federated learning Book Open access Nov 2026

FedCRA: Client Risk-aware Aggregation via Update Reconstruction for IoT-based Federated Learning

Federated Learning (FL) enables distributed model training without sharing raw data, making it particularly suitable for Internet of Things (IoT) environments. However, FL remains vulnerable to poisoning attacks, where malicious clients manipulate local updates to corrupt global model optimization. Existing defenses ma...

Jin Meng, S. Amitrano, Marzia Canzaniello et al. · ACM International Symposium... · 0 citations