Robust Unsupervised Flexible Auto-weighted Local-coordinate Concept Factorization for Image Clustering
international conference on acoustics speech and signal processing, pp. 2092-2096, 2019.
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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