The boundary labeling problem was recently introduced in [5] as a response to the problem of labeling dense point sets with large labels. In boundary labeling, we are given a recta...
Michael A. Bekos, Michael Kaufmann, Katerina Potik...
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such...
Over the last 25+ years, the software community has been searching for the best models for estimating variables of interest (e.g., cost, defects, and fault proneness). However, li...
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
In this paper, we present a constraint programming approach for the service consolidation problem that is being currently tackled by Neptuny, Milan. The problem is defined as: Giv...