Finding a path is harder than finding a tree

Authors:
Christopher Meek
Affiliations:
Microsoft Research, Redmond, WA
Venue:
Journal of Artificial Intelligence Research
Year:
2001

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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.