An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early research has shown that, in general, an ensemble of ...
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...
Abstract: Non-linear state estimation and some related topics, like parametric estimation, fault diagnosis, and perturbation attenuation, are tackled here via a new methodology in ...
We give a quick overview of some key issues in (quantitative) call center management: building realistic models, developing efficient tools to simulate these models, finding qui...
This paper deals with convex relaxations for quadratic distance problems, a class of optimization problems relevant to several important topics in the analysis and synthesis of ro...