Finding a Path is Harder than Finding a Tree

Computer Science – Artificial Intelligence

Scientific paper

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Scientific paper

10.1613/jair.914

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.

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