A Localization Approach to Improve Iterative Proportional Scaling in Gaussian Graphical Models
Computation
2010-07-22 v2 Methodology
Abstract
We discuss an efficient implementation of the iterative proportional scaling procedure in the multivariate Gaussian graphical models. We show that the computational cost can be reduced by localization of the update procedure in each iterative step by using the structure of a decomposable model obtained by triangulation of the graph associated with the model. Some numerical experiments demonstrate the competitive performance of the proposed algorithm.
Cite
@article{arxiv.0802.2581,
title = {A Localization Approach to Improve Iterative Proportional Scaling in Gaussian Graphical Models},
author = {Hisayuki Hara and Akimichi Takemura},
journal= {arXiv preprint arXiv:0802.2581},
year = {2010}
}
Comments
12 pages