A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis

Understand

Spectral clustering is one of the fundamental unsupervised learning methods widely used in data analysis.

• Sparse spectral clustering (SSC) imposes sparsity to the spectral clustering and it improves the interpretability of the model.
• This paper considers a widely adopted model for SSC, which can be formulated as an optimization problem over the Stiefel manifold with nonsmooth and nonconvex objective.
• Such an optimization problem is very challenging to solve.