Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework f...
Carmel Domshlak, Steven David Prestwich, Francesca...
In classical two-stage stochastic programming the expected value of the total costs is minimized. Recently, mean-risk models - studied in mathematical finance for several decades -...
In this paper, we present a method for constructing Loop’s subdivision surface patches with given G1 boundary conditions and a given topology of control polygon of the subdivisi...
Classical approaches to location problems are based on the minimization of the average distance (the median concept) or the minimization of the maximum distance (the center concept...