AIFeb 13, 2013
Binary Join Trees
arXiv:1302.3604v138 citations
AI Analysis
This work addresses a computational efficiency problem for users of probabilistic graphical models, but it appears incremental as it builds on existing architectures without claiming major breakthroughs.
The paper introduces binary join trees, a data structure designed to efficiently compute multiple marginals within the Shenoy-Shafer architecture, focusing on their definition, utility, and construction procedure.
The main goal of this paper is to describe a data structure called binary join trees that are useful in computing multiple marginals efficiently using the Shenoy-Shafer architecture. We define binary join trees, describe their utility, and sketch a procedure for constructing them.