Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
A genetic algorithm encoding is proposed which is able to automatically satisfy a class of important cardinality constraints where the set of distinct values of the design variabl...
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Exotic semirings such as the “(max, +) semiring” (R ∪ {−∞}, max, +), or the “tropical semiring” (N ∪ {+∞}, min, +), have been invented and reinvented many times s...
We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces [5]. We use the well-known fami...