In this paper, we propose a novel unsupervised algorithm, called Structure-Aware Subspace Clustering (SASC), to address the above issues. SASC considers local and global correlation structures simultaneously to
Clustering methods,Robustness,Clustering algorithms,Standards,Probabilistic logic,Optimization,Sparse matricesSubspace clustering is the problem of partitioning data drawn from a union of multiple subspaces. The most popular subspace clustering framework in recent years is the graph clustering-based approach, ...