On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
We bring together two recent trends in description logic (DL): lightweight DLs in which the subsumption problem is tractable and conservative extensions as a central tool for forma...
Traditional performance analysis of approximation algorithms considers overall performance, while economic fairness analysis focuses on the individual performance each user receiv...
We present a thorough study of Propositional Dynamic Logic over a variation of labeled transition systems, called accelerated labelled transition systems, which are transition sys...