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Complexity of Discrete Energy Minimization Problems
[article]
2016
arXiv
pre-print
Discrete energy minimization is widely-used in computer vision and machine learning for problems such as MAP inference in graphical models. The problem, in general, is notoriously intractable, and finding the global optimal solution is known to be NP-hard. However, is it possible to approximate this problem with a reasonable ratio bound on the solution quality in polynomial time? We show in this paper that the answer is no. Specifically, we show that general energy minimization, even in the
arXiv:1607.08905v1
fatcat:k5xddu3xvndnziljktxo5p4mpe