Visualizing Data as Objects by DC (Difference of Convex) Optimization

Emilio Carrizosa, Vanesa Guerrero, Dolores Romero Morales

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In this paper we address the problem of visualizing in a bounded region a set of individuals, which has attached a dissimilarity measure and a statistical value, as convex objects. This problem, which extends the standard Multidimensional Scaling Analysis, is written as a global optimization problem whose objective is the difference of two convex functions (DC). Suitable DC decompositions allow us to use the Difference of Convex Algorithm (DCA) in a very efficient way. Our algorithmic approach is used to visualize two real-world datasets.
Original languageEnglish
JournalMathematical Programming
Issue number1
Pages (from-to)119-140
Number of pages22
Publication statusPublished - May 2018

Bibliographical note

Published online: 28. April 2017.


  • Data visualization
  • DC functions
  • DC algorithm
  • Multidimensional scaling analysis

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