Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Manifold Proximal Linear Method for Sparse Spectral Clustering with
  Application to Single-Cell RNA Sequencing Data Analysis   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. Existing
methods usually solve its convex relaxation or need to smooth its nonsmooth
part using certain smoothing techniques. In this paper, we propose a manifold
proximal linear method (ManPL) that solves the original SSC formulation. We
also extend the algorithm to solve the multiple-kernel SSC problems, for which
an alternating ManPL algorithm is proposed. Convergence and iteration
complexity results of the proposed methods are established. We demonstrate the
advantage of our proposed methods over existing methods via the single-cell RNA
sequencing data analysis.

31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
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The categories of this paper are: eess
12
The categories of this paper are: nucl-th
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The categories of this paper are: solv-int
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The categories of this paper are: q-alg