We present a novel approach to constraintbased causal discovery, that takes the form of straightforward logical inference, applied to a list of simple, logical statements about ca...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Abstract: The article presents a model of the structural properties of virtual communities and the information they can access. It argues that a large part of the information – a...
The ability to discover the AS-level path between two end-points is valuable for network diagnosis, performance optimization, and reliability enhancement. Virtually all existing t...