$\ell_0$ -Motivated Low-Rank Sparse Subspace Clustering
$\ell_0$ -Motivated Low-Rank Sparse Subspace Clustering
In many applications, high-dimensional data points can be well represented by low-dimensional subspaces. To identify the subspaces, it is important to capture a global and local structure of the data which is achieved by imposing low-rank and sparseness constraints on the data representation matrix. In low-rank sparse subspace clustering (LRSSC), …