Sparse subspace-based clustering

Sparse subspace-based clustering is a data clustering technique that identifies low-dimensional subspace structures within high-dimensional data to effectively group data points. This method aims to leverage the sparsity and subspace properties of the data to enhance the accuracy and robustness of clustering. It is widely applied in areas such as image segmentation, signal processing, and bioinformatics, making it a valuable tool with significant practical importance.