On Reliable Multi-View Affinity Learning for Subspace Clustering
In multi-view subspace clustering, the low-rankness of the stacked self-representation tensor is widely accepted to capture the high-order cross-view correlation. However, using the nuclear norm as a convex surrogate of the rank function, the self-representation tensor exhibits strong connectivity w...
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Veröffentlicht in: | IEEE transactions on multimedia 2021, Vol.23, p.4555-4566 |
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Sprache: | eng |
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