Unsupervised Spectral Feature Selection With Dynamic Hyper-Graph Learning
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DOI: 10.1109/tkde.2020.3017250
Abstract: Unsupervised spectral feature selection (USFS) methods could output interpretable and discriminative results by embedding a Laplacian regularizer in the framework of sparse feature selection to keep the local similarity of the training samples. To do… read more here.
Keywords: hyper graph; graph; unsupervised spectral; feature selection ... See more keywords