# A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees

arXiv: https://arxiv.org/abs/1302.3558 · HTML: https://mlsanity.com/paper/1302.3558/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2013.

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

- [Neural Trees for Learning on Graphs](https://mlsanity.com/paper/2105.07264/) (2021)

## Abstract (arXiv)

An algorithm is developed for finding a close to optimal junction tree of a given graph G. The algorithm has a worst case complexity O(c^k n^a) where a and c are constants, n is the number of vertices, and k is the size of the largest clique in a junction tree of G in which this size is minimized. The algorithm guarantees that the logarithm of the size of the state space of the heaviest clique in the junction tree produced is less than a constant factor off the optimal value. When k = O(log n), our algorithm yields a polynomial inference algorithm for Bayesian networks.