Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization
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Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization
When multiple views of data are available for a set of subjects, co-clustering aims to identify subject clusters that agree across the different views. We explore the problem of co-clustering when the underlying clusters exist in different subspaces of each view. We propose a proximal alternating linearized minimization algorithm that ...
1.8K viewsSep 27, 2015
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