Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
We optimally place intrusion detection system (IDS) sensors and prioritize IDS alerts using attack graph analysis. We begin by predicting all possible ways of penetrating a networ...
Rule bases are common in many business rule applications, clinical decision support programs, and other types of intelligent systems. As the size of the rule bases grows and the in...
—Evidence shows that proposals for new modeling notations emerge and evolution of current ones are becoming more complex, often in an attempt to satisfy the many different modeli...
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...