An Objective Function for Belief Net Triangulation
Abstract
This paper presents a new approach to the triangulation of belief networks. Triangulation is a combinatorial optimization problem; our idea is to embed its discrete domain into a continuous domain e. Then, by suitably extending the objective function over e, we can make use of continuous optimization techniques to do the minimization. We used an upper bound of the total junction tree weight as the cost function. The appropriateness of this choice is discussed and explored by simulations.
Cite
Text
Meilă and Jordan. "An Objective Function for Belief Net Triangulation." Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, 1997.Markdown
[Meilă and Jordan. "An Objective Function for Belief Net Triangulation." Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, 1997.](https://mlanthology.org/aistats/1997/meila1997aistats-objective/)BibTeX
@inproceedings{meila1997aistats-objective,
title = {{An Objective Function for Belief Net Triangulation}},
author = {Meilă, Marina and Jordan, Michael I.},
booktitle = {Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics},
year = {1997},
pages = {355-362},
volume = {R1},
url = {https://mlanthology.org/aistats/1997/meila1997aistats-objective/}
}