We establish several approximate max-integral-flow / minmulticut theorems. While in general this ratio can be very large, we prove strong approximation ratios in the case where th...
Abstract The most common matching applications, e.g., ontology matching, focus on the computation of the correspondences holding between the nodes of graph structures (e.g., concep...
This paper introduces improved methodology to triangulate dynamic graphical models and dynamic Bayesian networks (DBNs). In this approach, a standard DBN template can be modified...
Abstract--In this paper, we present an efficient graph-based evolutionary optimization technique called evolutionary graph generation (EGG) and the proposed approach is applied to ...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...