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A Differential Semantics for Jointree Algorithms

Conference Paper Artificial Intelligence · Machine Learning

Abstract

A new approach to inference in belief networks has been recently proposed, which is based on an algebraic representation of belief networks using multi{linear functions. According to this approach, the key computational question is that of representing multi{linear functions compactly, since inference reduces to a simple process of ev aluating and difierentiating such functions. W e show here that mainstream inference algorithms based on jointrees are a special case of this approach in a v ery precise sense. W e use this result to prov e new properties of jointree algorithms, and then discuss some of its practical and theoretical implications.

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Context

Venue
Annual Conference on Neural Information Processing Systems
Archive span
1987-2025
Indexed papers
30776
Paper id
243898782929327490
v2026.09.13