Models of computer users that are learned on the basis of data can make use of two types of information: data about users in general and data about the current individual user. Fo...
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
Abstract. Network Intrusion Detection Systems (NIDS) aim at preventing network attacks and unauthorised remote use of computers. More accurately, depending on the kind of attack it...
Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an ...