CE-MVC combines NMI-based and conditional-entropy-based view weighting with per-view autoencoders, and reports top clustering accuracy on DIGIT, COIL, RGB-D, and Caltech.
Multiview spectral clustering via structured low-rank matrix factorization
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An Adaptive Framework for Multi-View Clustering Leveraging Conditional Entropy Optimization
CE-MVC combines NMI-based and conditional-entropy-based view weighting with per-view autoencoders, and reports top clustering accuracy on DIGIT, COIL, RGB-D, and Caltech.