# Algorithms for Learning Decomposable Models and Chordal Graphs

arXiv: https://arxiv.org/abs/1302.1524 · HTML: https://mlsanity.com/paper/1302.1524/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Feb 2013.

## Built on by (most cited first, 1 of 1)

- [Approximate Implication for Probabilistic Graphical Models](https://mlsanity.com/paper/2310.13942/) (2023)

## Abstract (arXiv)

Decomposable dependency models and their graphical counterparts, i.e., chordal graphs, possess a number of interesting and useful properties. On the basis of two characterizations of decomposable models in terms of independence relationships, we develop an exact algorithm for recovering the chordal graphical representation of any given decomposable model. We also propose an algorithm for learning chordal approximations of dependency models isomorphic to general undirected graphs.