Subspace Clustering with Irrelevant Features via Robust Dantzig Selector

NeurIPS 2015 Chao QuHuan Xu

This paper considers the subspace clustering problem where the data contains irrelevant or corrupted features. We propose a method termed ``robust Dantzig selector'' which can successfully identify the clustering structure even with the presence of irrelevant features... (read more)

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