On Difference of Convex Optimization to Visualize Statistical Data and Dissimilarities
Emilio Carrizosa, Vanesa Guerrero, Dolores Romero Morales · 2016
In this talk 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.