Multi-view clustering via canonical correlation analysis

  title={Multi-view clustering via canonical correlation analysis},
  author={Kamalika Chaudhuri and Sham M. Kakade and Karen Livescu and Karthik Sridharan},
  booktitle={ICML '09},
Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by projecting the data into a lower-dimensional subspace, e.g. via Principal Components Analysis (PCA) or random projections, before clustering. Here, we consider constructing such projections using multiple views of the data, via Canonical Correlation Analysis (CCA). Under the assumption that the views are un-correlated… 

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