Improved Moves for Truncated Convex Models

@article{Kumar2008ImprovedMF,
  title={Improved Moves for Truncated Convex Models},
  author={M. Pawan Kumar and Philip H. S. Torr},
  journal={Journal of Machine Learning Research},
  year={2008},
  volume={12},
  pages={31-67}
}
We consider the problem of obtaining the approximate maximu m a posterioriestimate of a discrete random field characterized by pairwise p ot ntials that form a truncated convex model. For this problem, we propose an impr oved st-MINCUT basedmove makingalgorithm. Unlike previous move making approaches, which either provide a loose bound or no bound on the quality of the s olution (in terms of the corresponding Gibbs energy), our algorithm achieves th same guarantees as the standard linear… CONTINUE READING
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Improved moves for truncate d convex models

  • M. P. Kumar, P.H.S. Torr
  • Technical report, University of Oxford,
  • 2008
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