Robust Unsupervised Flexible Auto-weighted Local-coordinate Concept Factorization for Image Clustering

international conference on acoustics speech and signal processing, pp. 2092-2096, 2019.

Cited by: 10|Bibtex|Views54|DOI:https://doi.org/10.1109/icassp.2019.8683263
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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

We investigate the high-dimensional data clustering problem by proposing a novel and unsupervised representation learning model called Robust Flexible Auto-weighted Local-coordinate Concept Factorization (RFA-LCF). RFA-LCF integrates the robust flexible CF, robust sparse local-coordinate coding and the adaptive reconstruction weighting ...More

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