Inference Algorithms for Similarity Networks
arXiv:1303.1493
Abstract
We examine two types of similarity networks each based on a distinct notion of relevance. For both types of similarity networks we present an efficient inference algorithm that works under the assumption that every event has a nonzero probability of occurrence. Another inference algorithm is developed for type 1 similarity networks that works under no restriction, albeit less efficiently.
Appears in Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (UAI1993)