This work casts the traffic analysis of anonymity systems, and in particular mix networks, in the context of Bayesian inference. A generative probabilistic model of mix network ar...
As access to information becomes more intensive in society, a great deal of that information is becoming available through diverse channels. Accordingly, users require effective ...
Bayesian Networks, BNs, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. This solution can be applied to identify the in...
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...