Maximum persistency via iterative relaxed inference with graphical models

@article{Shekhovtsov2015MaximumPV,
  title={Maximum persistency via iterative relaxed inference with graphical models},
  author={Alexander Shekhovtsov and P. Swoboda and Bogdan Savchynskyy},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2015},
  pages={521-529}
}
We consider the NP-hard problem of MAP-inference for graphical models. We propose a polynomial time practically efficient algorithm for finding a part of its optimal solution. Specifically, our algorithm marks each label in each node of the considered graphical model either as (i) optimal, meaning that it belongs to all optimal solutions of the inference problem; (ii) non-optimal if it provably does not belong to any solution; or (iii) undefined, which means our algorithm can not make a… Expand
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