Abstract. We develop a model of Parametric Probabilistic Transition Systems, where probabilities associated with transitions may be parameters. We show how to find instances of th...
Ruggero Lanotte, Andrea Maggiolo-Schettini, Angelo...
:In this paper, a novel supervised dimensionality reduction method is developed based on both the correlation analysis and the idea of large margin learning. The method aims to m...
When we model a phenomenon we apply a perspective on the phenomenon. The perspective decides which properties we include in the model. It also decides how we conceive a phenomenon ...
Recent work on anonymizing online social networks (OSNs) has looked at privacy preserving techniques for publishing a single instance of the network. However, OSNs evolve and a si...
Smriti Bhagat, Graham Cormode, Balachander Krishna...
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...