Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
— Integrating information coming from different sensors is a fundamental capability for autonomous robots. For complex tasks like topological localization, it would be desirable ...
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
A new framework for the context and speaker independent recognition of emotions from voice, based on a richer and more natural representation of the speech signal, is proposed. Th...
One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...