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References

[1]  
" Brainweb: Simulated brain database. "
http://brainweb.bic.mni.mcgill.ca/brainweb/.
[2]  
"The probabilistic inference challenge (PIC2011). "
http://www.cs.huji.ac.il/project/PASCAL/.
[3]  Kroeger, Thorben and Kappes, Jörg Hendrik and Beier, Thorsten and Koethe,Ulrich and Hamprecht, Fred A
"Asymmetric Cuts: Joint Image Labeling and Partitioning"
36th German Conference on Pattern Recognition, 2014
[4]  Kappes, Jörg Hendrik and Beier, Thorsten and Schnöorr, Christoph
"MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves"
International Workshop on Graphical Models in Computer Vision, 2014
[5]  Jörg H. Kappes and Bjoern Andres and Fred A. Hamprecht and Christoph Schnörr and Sebastian Nowozin and Dhruv Batra and Sungwoong Kim and Bernhard X. Kausler and Thorben Kröger and Jan Lellmann and Nikos Komodakis and Bogdan Savchynskyy and Carsten Rother
"A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems"
CoRR, 2014
[6]  Lena Gorelick, Yuri Boykov, Olga Veksler, Ismail Ben Ayed and Andrew Delong
"Submodularization for Binary Pairwise Energies "
In Computer Vision and Pattern Recognition(CVPR), Columbus, Ohio, June 2014.
[7]  Stefan Roth and Michael J. Black
"Field of Experts"
International Journal of Computer Vision (IJCV), 82(2):205-229, April 2009.
[8]  Jaimovich, A., Meshi, O., Friedman, N.
"Template based inference in symmetric relational markov random fields"
In: Proceedings of the Twenty-Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-07), pp. 191-199. AUAI Press, Corvallis, Oregon (2007)
[9]  Jaimovich, Ariel and Elidan, Gal and Margalit, Hanah and Friedman, Nir
"Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach."
Journal of Computational Biology 13(2), pp. 145-164. (2007)
[10]   Yanover, C., Schueler-Furman, O., Weiss, Y.
"Minimizing and learning energy functions for side-chain prediction"
Journal of Computational Biology 15(7), 899-911 (2008).
[11]  Brandes, U., Delling, D., Gaertler, M., Goerke, R., Hoefer, M., Nikoloski, Z., Wagner, D.
"On modularity clustering"
IEEE Transactions on Knowledge and Data Engineering 20(2), 172-188 (2008).
[12]  David Sontag, Do Kook Choe, and Yitao Li
"Efficiently Searching for Frustrated Cycles in MAP Inference."
Uncertainty in Artificial Intelligence (UAI) 28. Catalina Island, United States. 2012.
[13]  David Sontag, Talya Meltzer, Amir Globerson, Tommi Jaakkola and Yair Weiss
"Tightening LP Relaxations for MAP using Message Passing"
Uncertainty in Artificial Intelligence (UAI). Helsinki, Finland. 2008.
[14]  Amir Globerson, Tommi Jaakkola
"Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations"
Advances in Neural Information Processing Systems (NIPS) 21. Vancouver, Canada. 2007.
[15]  Lars Otten and Rina Dechter
"Anytime AND/OR Depth-first Search for Combinatorial Optimization."
In AI Communications, Volume 25 (3), pages 211-227, 2012.
[16]  Andre F. T. Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, and Ma¡rio A. T. Figueiredo.
"Augmented Dual Decomposition for MAP Inference."
NIPS Workshop in Optimization for Machine Learning, Whistler, Canada, December 2010.
[17]  Savchynskyy Bogdan and Kappes, Joerg and Swoboda, Paul and Schnoerr, Cristoph
"Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation"
In Advances in Neural Information Processing Systems (NIPS) 2013.
[18]  A. Agarwala, M. Dontcheva, M. Agrawala, S. Drucker, A. Colburn, B. Curless, D. Salesin, and M. Cohen.
"Interactive digital photomontage. "
ACM Transactions on Graphics, 2004.
[19]  K. Alahari, P. Kohli, and P.H.S. Torr
"Dynamic Hybrid Algorithms for MAP Inference in Discrete MRFs"
IEEE PAMI 2010
[20]  B. Andres, J. H. Kappes, T. Beier, U. Köthe, and F. A. Hamprecht.
" Probabilistic image segmentation with closedness constraints. "
In ICCV, 2011.
[21]  B. Andres, J. H. Kappes, U. Köthe, C. Schnörr, and F. A. Hamprecht.
"An empirical comparison of inference algorithms for graphical models with higher order factors using OpenGM. "
In DAGM, pages 353-362, 2010.
[22]  B. Andres, U. Köthe, T. Kroeger, M. Helmstaedter, K. L. Briggman, W. Denk, and F. A. Hamprecht.
"3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries. "
Medical Image Analysis, 16(4):796-805, 2012.
[23]  B. Andres, T. Kröger, K. L. Briggman, W. Denk, N. Korogod, G. Knott, U. Köthe, and F. A. Hamprecht. "
"Globally optimal closed-surface segmentation for connectomics.
In ECCV, 2012.
[24]  B. Andres, B. T., and J. H. Kappes.
"OpenGM: A C++ library for discrete graphical models. "
ArXiv e-prints, 2012.
[25]  M. Bergtholdt, J. H. Kappes, S. Schmidt, and C. Schnörr.
"A study of parts-based object class detection using complete graphs. "
IJCV, 87(1-2):93-117, 2010.
[26]  J. Besag
"On the statistical analysis of dirty pictures."
Journal of the Royal Statistical Society, Series B, 48:259--302.
[27]  S. Birchfield and C. Tomasi.
"A pixel dissimilarity measure that is insensitive to image sampling. "
IEEE Trans. Pattern Anal. Mach. Intell., 20(4):401-406, 1998.
[28]  Y. Boykov.
"Computing geodesics and minimal surfaces via graph cuts. "
In ICCV, 2003.
[29]  Y. Boykov and V. Kolmogorov.
"An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. "
IEEE PAMI, 26(9):1124-1137, 2004.
[30]  Y. Boykov, O. Veksler, and R. Zabih.
"Fast approximate energy minimization via graph cuts. "
IEEE PAMI, 23(11):1222-1239, 2001.
[31]  A. Chambolle, D. Cremers, and T. Pock.
"A convex approach to minimal partitions. "
J. Imaging Sci., 5(4):1113-1158, 2012.
[32]  S. Chopra and M. R. Rao.
"The partition problem. "
Math. Program, 59:87-115, 1993.
[33]  P. F. Felzenszwalb and D. P. Huttenlocher.
"Efficient belief propagation for early vision. "
Int. J. Comput. Vision, 70(1):41-54, Oct. 2006.
[34]  A. Fix, A. Gruber, E. Boros, R. Zabih
"A graph cut algorithm for higher-order Markov Random Fields."
ICCV 2011: 1020-1027
[35]   A. C. Gallagher, D. Batra, and D. Parikh.
"Inference for order reduction in Markov random fields. "
In CVPR, 2011.
[36]  S. Geman and D. Geman
"Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images."
IEEE-PAMI, 6, 1984, 721-741.
[37]  S. Gould, R. Fulton, and D. Koller.
"Decomposing a scene into geometric and semantically consistent regions. "
In ICCV, 2009.
[38]  D. Hoiem, A. A. Efros, and M. Hebert.
"Recovering surface layout from an image. "
IJCV, 75(1), 2007.
[39]  K. Jung, P. Kohli and D. Shah
"Local Rules for Global MAP: When Do They Work?"
NIPS 2009.
[40]  J. H. Kappes, M. Speth, C. Reinelt, and C. Schnörr,
"Higher-order Segmentation via Multicuts."
In ArXiv e-prints, 2013
[41]  J. H. Kappes, M. Speth, C. Reinelt, and C. Schnörr,
"Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization"
In CVPR, 2013
[42]  J. H. Kappes, B. Andres, F.A. Hamprecht, C. Schnörr, S. Nowozin, D. Batra, S. Kim, B.X. Kausler, J. Lellmann, N. Komodakis, and C. Rother.
"A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems"
In CVPR, 2013
[43]  J. H. Kappes.
"Inference on Highly-Connected Discrete Graphical Models with Applications to Visual Object Recognition."
doctoral thesis, Ruprecht-Karls-Universität Heidelberg, Faculty of Mathematics and Computer Sciences, Heidelberg, Germany, 2011.
[44]  J. H. Kappes, B. Savszinskyy, and C. Schnörr.
"A bundle approach to efficient MAP-inference by Lagrangian relaxation."
In CVPR, 2012.
[45]  J. H. Kappes, M. Speth, B. Andres, G. Reinelt, and C. Schnörr.
"Globally optimal image partitioning by multicuts. "
In EMMCVPR, 2011.
[46]  B. X. Kausler, M. Schiegg, B. Andres, M. Lindner, H. Leitte, L. Hufnagel, U. Köthe, and F. A. Hamprecht.
"A discrete chain graph model for 3d+t cell tracking with high misdetection robustness. "
In ECCV, 2012.
[47]  B.W. Kernighan and S. Lin
"An efficient heuristic procedure for partitioning graphs."
Bell Systems Technical Journal 49: 291-307.
[48]  S. Kim, S. Nowozin, P. Kohli, and C. D. Yoo.
"Higher-order correlation clustering for image segmentation."
In NIPS. 2011.
[49]  T. Kim, S. Nowozin, P. Kohli, and C. D. Yoo.
"Variable grouping for energy minimization. "
In CVPR, 2011.
[50]  P. Kohli, A. Shekhovtsov, C. Rother, V. Kolmogorov, and P. H. S. Torr
"On partial optimality in multi-label MRFs"
ICML 2008: 480-487
[51]  V. Kolmogorov.
"Convergent tree-reweighted message passing for energy minimization. "
PAMI, 28(10):1568­1583, 2006.
[52]  V. Kolmogorov and R. Zabih.
"What energy functions can be minimized via graph cuts? "
In ECCV, 2002.
[53]  N. Komodakis and G. Tziritas.
"Approximate labeling via graph cuts based on linear programming. "
IEEE PAMI, 29(8):1436-1453, 2007.
[54]  N. Komodakis and N. Paragios
"Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles"
ECCV 2008
[55]  F.R. Kschischang, B.J. Frey, and H-A. Loeliger
"Factor Graphs and the Sum-Product Algorithm"
IEEE Transactions on Information Theory 47 (2): 498-519
[56]  J. Lellmann, and C. Schnörr
"Continuous Multiclass Labeling Approaches and Algorithms
SIAM J.~Imag.~Sci., 2011.
[57]  J. M. Mooij
"libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models "
Journal of Machine Learning Research, 11:2169-2173,2010
[58]  S. Nowozin, C. Rother, S. Bagon, T. Sharp, B. Yao, and P. Kohli
"Decision tree fields"
ICCV 2011
[59]  L. Otten and R. Dechter.
"Anytime AND/OR depth-first search for combinatorial optimization. "
2011.
[60]  C. Rother, V. Kolmogorov, V. S. Lempitsky, and M. Szummer.
"Optimizing binary MRFs via extended roof duality. "
In CVPR, 2007.
[61]  B. Savchynskyy, S. Schmidt, J. H. Kappes, C. Schnörr
"Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing"
In UAI, 2012
[62]  R. H. Swendsen and J. Wang
"Nonuniversal critical dynamics in Monte Carlo simulations."
Phys. Rev. Lett., 58(2):86-88, 1987.
[63]  P. Swoboda, B. Savchynskyy, J. H. Kappes, and c. Schnörr,
"Partial Optimality via Iterative Pruning for the Potts Model"
In SSVM, 2013
[64]  R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother.
"A comparative study of energy minimization methods for Markov random fields with smoothness-based priors. "
IEEE PAMI, 30(6):1068-1080, 2008.
[65]  M. F. Tappen and W. T. Freeman.
"Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters. "
In ICCV, 2003
[66]  M. J. Wainwright, T. Jaakkola, and A. S. Willsky.
"MAP estimation via agreement on trees: message-passing and linear programming. "
IEEE Trans. Inf. Theory, 51(11):3697-3717, 2005.


 
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