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...