Inference Algorithms for Similarity Networks

Dan Geiger; David Heckerman

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arXiv · 1303.1493

Inference Algorithms for Similarity Networks

Dan Geiger·David Heckerman

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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.

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Dan Geiger, David Heckerman. 2013-03-06. Inference Algorithms for Similarity Networks. https://arxiv.org/abs/1303.1493

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