@inproceedings{PrusaWernerCVPR2013,
  IS = { zkontrolovano 24 Jan 2014 },
  UPDATE  = { 2013-09-25 },
  author = {Pr{\r u}{\v s}a, Daniel and Werner, Tom{\' a}{\v s}},
  title = {Universality of the Local Marginal Polytope},
  booktitle = {CVPR: 2013 IEEE Computer Society Conference on Computer 
    Vision and Pattern Recognition},
  book_pages = {3735},
  pages = {1738--1743},
  publisher = {IEEE Computer Society},
  address = {Los Alamitos, USA},
  issn = {1063-6919},
  year = {2013},
  month = {June},
  day = {25-27},
  venue = {Portland, OR, US},
  annote = {We show that solving the LP relaxation of the MAP
    inference problem in graphical models (also known as the min-sum
    problem, energy minimization, or weighted constraint satisfaction)
    is not easier than solving any LP.  More precisely, any polytope
    is linear-time representable by a local marginal polytope and any
    LP can be reduced in linear time to a linear optimization
    (allowing infinite weights) over a local marginal polytope.},
  keywords = {graphical models, energy minimization, 
    linear programming relaxation},
  prestige = {important},
  note = {CD-ROM},
  doi = {10.1109/CVPR.2013.227},
  psurl = {[PrusaWernerCVPR2013.pdf]},
  project = {GACR P202/12/2071, FP7-ICT-247525 HUMAVIPS, FP7-ICT-270138 DARWIN},
}