Scalable Sparse Subspace Clustering via Ordered Weighted $\ell_1$ Regression

10 Jul 2018 Urvashi Oswal Robert Nowak

The main contribution of the paper is a new approach to subspace clustering that is significantly more computationally efficient and scalable than existing state-of-the-art methods. The central idea is to modify the regression technique in sparse subspace clustering (SSC) by replacing the $\ell_1$ minimization with a generalization called Ordered Weighted $\ell_1$ (OWL) minimization which performs simultaneous regression and clustering of correlated variables... (read more)

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