Abstract We propose an alternative notion of asymptotic behaviors for the study of type2 computational complexity. Since the classical asymptotic notion (for all but finitely many...
We argue that in a distributed context, such as the Semantic Web, ontology engineers and data creators often cannot control (or even imagine) the possible uses their data or ontolo...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
Detecting the dominant normal directions to the decision surface is an established technique for feature selection in high dimensional classification problems. Several approaches...
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Abstract. Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Ny...