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Original paper

Multi-view subspace clustering via simultaneously learning the representation tensor and affinity matrix

Volume: 106, Pages: 107441 - 107441
Published: May 16, 2020
Abstract
Multi-view subspace clustering aims at separating data points into multiple underlying subspaces according to their multi-view features. Existing low-rank tensor representation-based multi-view subspace clustering algorithms are robust to noise and can preserve the high-order correlations of multi-view features. However, they may suffer from two common problems: (1) the local structures and different importance of each view feature are often...
Paper Details
Title
Multi-view subspace clustering via simultaneously learning the representation tensor and affinity matrix
Published Date
May 16, 2020
Volume
106
Pages
107441 - 107441
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