Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
Motivation: Most previous approaches to model biochemical networks havefocusedeither on the characterization of a networkstructurewith a number of components or on the estimation ...
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
Nowadays, Network Intrusion Detection Systems are quickly updated in order to prevent systems against new attacks. This situation has provoked that attackers focus their efforts on...