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.
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