Data clustering based on the modified relaxation Cheeger cut model

DOI10.1007/s40314-022-01757-xzbMath1499.65249OpenAlexW4210520830MaRDI QIDQ2115038

Yanyan Li

Publication date: 15 March 2022

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40314-022-01757-x

zbMATH Keywords

Rayleigh quotientdata clusteringalternating direction of method of multipliersratio Cheeger cutratio normalized cut

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• UCI-ml
• AS 136

Cites Work

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• Algorithm AS 136: A K-Means Clustering Algorithm
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• Modified Cheeger and ratio cut methods using the Ginzburg–Landau functional for classification of high-dimensional data
• Rayleigh quotient minimization for absolutely one-homogeneous functionals
• On the Partial Difference Equations of Mathematical Physics
• On Nonlinear Fractional Programming
• Lower Bounds for the Partitioning of Graphs

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