Beyond Low-Rank Representations: Orthogonal Clustering Basis Reconstruction with Optimized Graph Structure for Multi-view Spectral Clustering

Neural Networks, Volume abs/1708.02288, 2018, Pages 1-8.

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Keywords:
ClusteringLow-Rank RepresentationMulti-view subspace learning

Abstract:

Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view coun...More

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