Robust Subspace Recovery via Bi-Sparsity Pursuit

  title={Robust Subspace Recovery via Bi-Sparsity Pursuit},
  author={Xiao Bian and Hamid Krim},
Successful applications of sparse models in computer vision and machine learning [3][2][5] imply that in many real-world applications, high dimensional data is distributed in a union of low dimensional subspaces. Nevertheless, the underlying structure may be affected by sparse errors and/or outliers. In this paper, we propose a dual sparse model as a framework to analyze this problem and provide a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We further… CONTINUE READING