— An iterative feature selection method based on feature typicality and interactivity analysis is presented in this paper. The aim is to enhance model interpretability by selecti...
Cyril Mazaud, Jan Rendek, Vincent Bombardier, Laur...
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
Eric van den Berg, Praveen Gopalakrishnan, Byungsu...
Abstract. Most test-selection algorithms currently in use with probabilistic networks select variables myopically, that is, test variables are selected sequentially, on a one-by-on...
Abstract. This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric m...
A common problem in genetic programming search algorithms is destructive crossover in which the offspring of good parents generally has worse performance than the parents. Design...