A fast anchor-based graph-regularized low-rank representation approach for large-scale subspace clustering

Lili Fan; Gui‐Fu Lu; Ganyi Tang; Yong Wang

doi:10.1007/s00138-023-01487-y

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A fast anchor-based graph-regularized low-rank representation approach for large-scale subspace clustering

Lili Fan Gui‐Fu Lu Ganyi Tang Yong Wang

Year: 2023 Journal: Machine Vision and Applications Vol: 35 (1) Publisher: Springer Science+Business Media

DOI: 10.1007/s00138-023-01487-y

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Keywords:

Cluster analysis Rank (graph theory) Graph Computer science Representation (politics) Scale (ratio) Subspace topology Pattern recognition (psychology) Mathematics Artificial intelligence Theoretical computer science Combinatorics Geography Cartography

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Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Face and Expression Recognition

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Medical Image Segmentation Techniques

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A fast anchor-based graph-regularized low-rank representation approach for large-scale subspace clustering

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