Volume 33, Issue 5
The 1-Laplacian Cheeger Cut: Theory and Algorithms

K.C. Chang, Sihong ShaoDong Zhang

J. Comp. Math., 33 (2015), pp. 443-467.

Published online: 2015-10

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  • Abstract

This paper presents a detailed review of both theory and algorithms for the Cheeger cut based on the graph 1-Laplacian. In virtue of the cell structure of the feasible set, we propose a cell descend (CD) framework for achieving the Cheeger cut. While plugging the relaxation to guarantee the decrease of the objective value in the feasible set, from which both the inverse power (IP) method and the steepest descent (SD) method can also be recovered, we are able to get two specified CD methods. Comparisons of all these methods are conducted on several typical graphs.

  • Keywords

Spectral graph theory, Spectral clustering, 1-Laplace operator, Graph Laplacian, Eigenvalue problems, Cheeger constant, Graph cut, Optimization, Convergence

  • AMS Subject Headings

05C85, 05C50, 05C35, 58C40, 90C27, 35P30, 05C75, 90C26, 90C35.

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

kcchang@math.pku.edu.cn (K.C. Chang)

sihong@math.pku.edu.cn (Sihong Shao)

dongzhang@pku.edu.cn (Dong Zhang)

  • BibTex
  • RIS
  • TXT
@Article{JCM-33-443, author = {Chang , K.C. and Shao , Sihong and Zhang , Dong}, title = {The 1-Laplacian Cheeger Cut: Theory and Algorithms}, journal = {Journal of Computational Mathematics}, year = {2015}, volume = {33}, number = {5}, pages = {443--467}, abstract = {

This paper presents a detailed review of both theory and algorithms for the Cheeger cut based on the graph 1-Laplacian. In virtue of the cell structure of the feasible set, we propose a cell descend (CD) framework for achieving the Cheeger cut. While plugging the relaxation to guarantee the decrease of the objective value in the feasible set, from which both the inverse power (IP) method and the steepest descent (SD) method can also be recovered, we are able to get two specified CD methods. Comparisons of all these methods are conducted on several typical graphs.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1506-m2014-0164}, url = {http://global-sci.org/intro/article_detail/jcm/9854.html} }
TY - JOUR T1 - The 1-Laplacian Cheeger Cut: Theory and Algorithms AU - Chang , K.C. AU - Shao , Sihong AU - Zhang , Dong JO - Journal of Computational Mathematics VL - 5 SP - 443 EP - 467 PY - 2015 DA - 2015/10 SN - 33 DO - http://doi.org/10.4208/jcm.1506-m2014-0164 UR - https://global-sci.org/intro/article_detail/jcm/9854.html KW - Spectral graph theory, Spectral clustering, 1-Laplace operator, Graph Laplacian, Eigenvalue problems, Cheeger constant, Graph cut, Optimization, Convergence AB -

This paper presents a detailed review of both theory and algorithms for the Cheeger cut based on the graph 1-Laplacian. In virtue of the cell structure of the feasible set, we propose a cell descend (CD) framework for achieving the Cheeger cut. While plugging the relaxation to guarantee the decrease of the objective value in the feasible set, from which both the inverse power (IP) method and the steepest descent (SD) method can also be recovered, we are able to get two specified CD methods. Comparisons of all these methods are conducted on several typical graphs.

K.C. Chang, Sihong Shao & Dong Zhang. (2020). The 1-Laplacian Cheeger Cut: Theory and Algorithms. Journal of Computational Mathematics. 33 (5). 443-467. doi:10.4208/jcm.1506-m2014-0164
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