Multi-View Subspace Clustering based on Tensor Schatten-p Norm

In this paper, we focus on the multi-view clustering problem. A novel multi-view clustering framework, called multi-view subspace clustering based on tensor Schatten-p norm (MVSC-TSP), is proposed for clustering task. In our method, the tensor Schatten-p norm, which is based on tensor singular value decomposition, is utilized to explore the global low-rank structure of multi-view self-representations. Since 0

Keywords:

• Cluster analysis
• Norm (mathematics)
• Matrix norm
• norm minimization
• Singular value decomposition
• Computer science
• Tensor
• Applied mathematics
• Data mining
• subspace clustering
• soft thresholding

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