640 search results - page 18 / 128 » Learning Programs in Different Paradigms using Genetic Progr... |
CORR
2006
Springer
13 years 8 months ago
2006
Springer
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...
CEC
2010
IEEE
13 years 6 months ago
2010
IEEE
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...
ICTAI
2009
IEEE
14 years 3 months ago
2009
IEEE
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
ICDM
2005
IEEE
14 years 2 months ago
2005
IEEE
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...
PLSA
1994
14 years 21 days ago
1994
Computer language paradigms offer linguistic abstractions and proof theories for expressing program implementations. Similarly, system architectures offer the hardware abstractions...