Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consi...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
Abstract—It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier’s accura...
Abstract. Partially ordered feature sets appear naturally in many classification settings with structured input instances, for example, when the data instances are graphs and a fe...
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...