Simplifying Scalable Subspace Clustering and Its Multi-View Extension by Anchor-to-Sample Kernel

As we all known, sparse subspace learning can provide good input for spectral clustering, thereby producing high-quality cluster partitioning. However, it employs complete samples as the dictionary for representation learning, resulting in non-negligible computational costs. Therefore, replacing the...

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Publié dans:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 34(2025) vom: 05., Seite 5084-5098
Auteur principal:	Lu, Zhoumin (Auteur)
Autres auteurs:	Nie, Feiping, Ma, Linru, Wang, Rong, Li, Xuelong
Format:	Article en ligne
Langue:	English
Publié:	2025
Accès à la collection:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sujets:	Journal Article