Interpretable nonconvex submodule clustering algorithm using ℓr-induced tensor nuclear norm and ℓ2,p column sparse norm with global convergence guarantees

Open Access

Peer-reviewed

Research Article

Interpretable nonconvex submodule clustering algorithm using ℓ_r-induced tensor nuclear norm and ℓ_2,p column sparse norm with global convergence guarantees

Ming Yang

Roles Conceptualization, Funding acquisition, Methodology, Validation

Affiliation School of Mathematical Sciences, Harbin Engineering University, Harbin, China

Shumao Han

Roles Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Mathematical Sciences, Harbin Engineering University, Harbin, China

Linglong Chen

Roles Investigation, Visualization, Writing – review & editing

Affiliation School of Mathematical Sciences, Harbin Engineering University, Harbin, China

Jiayi Wang

Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

Affiliation School of Mathematical Sciences, Harbin Engineering University, Harbin, China

The authors have declared that no competing interests exist.

Algorithms
Is the Subject Area "Algorithms" applicable to this article?

Thanks for your feedback.
Subspace clustering
Is the Subject Area "Subspace clustering" applicable to this article?

Thanks for your feedback.
Imaging techniques
Is the Subject Area "Imaging techniques" applicable to this article?

Thanks for your feedback.
Optimization
Is the Subject Area "Optimization" applicable to this article?

Thanks for your feedback.
Face
Is the Subject Area "Face" applicable to this article?

Thanks for your feedback.
Singular value decomposition
Is the Subject Area "Singular value decomposition" applicable to this article?

Thanks for your feedback.
Clustering algorithms
Is the Subject Area "Clustering algorithms" applicable to this article?

Thanks for your feedback.
Fourier analysis
Is the Subject Area "Fourier analysis" applicable to this article?

Thanks for your feedback.