Finding a Path is Harder than Finding a Tree
Artificial Intelligence
2011-06-10 v1
Abstract
I consider the problem of learning an optimal path graphical model from data and show the problem to be NP-hard for the maximum likelihood and minimum description length approaches and a Bayesian approach. This hardness result holds despite the fact that the problem is a restriction of the polynomially solvable problem of finding the optimal tree graphical model.
Cite
@article{arxiv.1106.1799,
title = {Finding a Path is Harder than Finding a Tree},
author = {C. Meek},
journal= {arXiv preprint arXiv:1106.1799},
year = {2011}
}