Greedy Approach for Subspace Clustering from Corrupted and Incomplete Data

2013/04/15 by Alexander Petukhov, Petukhov, Alexander, Inna Kozlov +1
Computer Science · Engineering · #65F99 #Advanced Clustering Algorithms Research #FOS: Mathematics #Face and Expression Recognition #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques

paper · pdf · doi:10.48550/arxiv.1304.4282

openalex publication_date 2013/04/15 · openalex created_date 2019/06/27 · openalex updated_date 2026/08/01

Abstract

We describe the Greedy Sparse Subspace Clustering (GSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces from incomplete corrupted and noisy data. We provide numerical evidences that, even in the simplest implementation, the greedy approach increases the subspace clustering capability of the existing state-of-the art SSC algorithm significantly.

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