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

Emilio Carrizosa, Vanesa Guerrero, Dolores Romero Morales

Research output: Working paperResearchpeer-review


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. 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 DCA algorithm in a very efficient way. Our algorithmic approach is used to visualize two real-world datasets.
Original languageEnglish
Place of PublicationMadison, WI
PublisherMathematical Optimization Society
Number of pages19
Publication statusPublished - 2015
SeriesOptimization Online


  • Data Visualization
  • DC functions
  • DC algorithm
  • Multidimensional Scaling Analysis

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