Unsupervised feature selection via low-rank approximation and structure learning

Shiping Wang; Han Wang

doi:10.1016/j.knosys.2017.03.002

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Unsupervised feature selection via low-rank approximation and structure learning

Shiping Wang Han Wang

Year: 2017 Journal: Knowledge-Based Systems Vol: 124 Pages: 70-79 Publisher: Elsevier BV

DOI: 10.1016/j.knosys.2017.03.002

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Keywords:

Computer science Dimensionality reduction Matrix decomposition Feature selection Feature learning Artificial intelligence Curse of dimensionality Cluster analysis Rank (graph theory) Regularization (linguistics) Machine learning Unsupervised learning Feature (linguistics) Pattern recognition (psychology) Mathematics

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Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Unsupervised feature selection via low-rank approximation and structure learning

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