We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
Location-based services (LBS) constitute an emerging application domain involving spatio-temporal databases. In this paper, i) we propose a classification of LBS, depending on whet...
Kostas Gratsias, Elias Frentzos, Vasilis Delis, Ya...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Edition is an important and useful task in supervised classification specifically for instance-based classifiers because edition discards from the training set those useless or har...
This paper describes a pilot study of a computer simulation called WIIS, which is designed to extend students' learning experience of the sizes of the objects beyond human vi...