In this paper, we present a memetic algorithm with novel local optimizer hybridization strategy for constrained optimization. The developed MA consists of multiple cycles. In each ...
In the 21st century it is becoming increasingly common to work and learn in teams that are globally distributed. Such teams rely heavily on ICT to facilitate communication. There ...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Ordinal classification is a form of multi-class classification where there is an inherent ordering between the classes, but not a meaningful numeric difference between them. Althou...
We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...