Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views

Neural Information Processing Systems 

Recently, federated multi-view clustering (FedMVC) has emerged to explore cluster structures in multi-view data distributed on multiple clients. Many existing approaches tend to assume that clients are isomorphic and all of them belong to either single-view clients or multi-view clients.

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