Multi-view Regression Clustering via Low-Rank Manifold Decomposition
Multi-view Clustering via Manifold Decomposition is proposed, which directly infers cluster labels from multi-view data without explicit similarity graph construction or anchor selection, and reformulates multi-view clustering as a unified multi-view regression problem, where cluster labels are optimized as model variables.