There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
— In service-oriented environments, reputation-based service selection is gaining increasing prominence. We propose in this paper a social network-based approach to model and ana...
— The main characterisrics of ad hoc networks are the lack of predefined infrastructure and the dynamic topology. These characteristics present some new security vulnerabilities...
Yacine Rebahi, Vicente E. Mujica V, Dorgham Sisale...
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...