A DC optimization-based clustering technique for edge detection

DOI10.1007/s11590-016-1031-7zbMath1366.90170OpenAlexW2343766162WikidataQ62473062 ScholiaQ62473062MaRDI QIDQ519782

Manlio Gaudioso, Annabella Astorino, Walaa Khalaf, Paolo D'Alessandro

Publication date: 5 April 2017

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11590-016-1031-7

zbMATH Keywords

classificationclusteringedge detectionDC optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26)

Related Items

Classification in the multiple instance learning framework via spherical separation ⋮ A bundle-type method for nonsmooth DC programs ⋮ Ellipsoidal classification via semidefinite programming ⋮ Sequential difference-of-convex programming ⋮ A clustering heuristic to improve a derivative-free algorithm for nonsmooth optimization ⋮ An augmented subgradient method for minimizing nonsmooth DC functions ⋮ DC programming and DCA: thirty years of developments ⋮ Proximal bundle methods for nonsmooth DC programming ⋮ An inertial algorithm for DC programming ⋮ Polyhedral separation via difference of convex (DC) programming

Cites Work

• DC models for spherical separation
• A fixed-center spherical separation algorithm with kernel transformations for classification problems
• New and efficient DCA based algorithms for minimum sum-of-squares clustering
• Margin maximization in spherical separation
• Edge detection by spherical separation
• A D.C. Optimization Algorithm for Solving the Trust-Region Subproblem
• Ellipsoidal separation for classification problems
• Polyhedral separability through successive LP
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