Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
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...
Computer language paradigms offer linguistic abstractions and proof theories for expressing program implementations. Similarly, system architectures offer the hardware abstractions...
Diomidis Spinellis, Sophia Drossopoulou, Susan Eis...