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52 Publications

2018 | Conference Paper | IST-REx-ID: 273   OA
Mohapatra P, Rolinek M, Jawahar CV, Kolmogorov V, Kumar MP. 2018. Efficient optimization for rank-based loss functions. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition 3693–3701.
View | DOI | Download (ext.) | arXiv
 
2018 | Research Data | IST-REx-ID: 5573   OA
Alhaija H, Sellent A, Kondermann D, Rother C. 2018. Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow, IST Austria,p.
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2017 | Conference Paper | IST-REx-ID: 1192   OA
Kazda A, Kolmogorov V, Rolinek M. 2017. Even delta-matroids and the complexity of planar Boolean CSPs. SODA: Symposium on Discrete Algorithms 307–326.
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2017 | Conference Paper | IST-REx-ID: 915   OA
Swoboda P, Andres B. 2017. A message passing algorithm for the minimum cost multicut problem. CVPR: Computer Vision and Pattern Recognition vol. 2017. 4990–4999.
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2017 | Journal Article | IST-REx-ID: 644   OA
Kolmogorov V, Krokhin A, Rolinek M. 2017. The complexity of general-valued CSPs. SIAM Journal on Computing. 46(3), 1087–1110.
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2017 | Conference Paper | IST-REx-ID: 916   OA
Swoboda P, Rother C, Abu Alhaija C, Kainmueller D, Savchynskyy B. 2017. A study of lagrangean decompositions and dual ascent solvers for graph matching. CVPR: Computer Vision and Pattern Recognition vol. 2017. 7062–7071.
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2017 | Thesis | IST-REx-ID: 992   OA
Rolinek M. 2017. Complexity of constraint satisfaction, IST Austria, 97p.
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2017 | Conference Paper | IST-REx-ID: 917   OA
Swoboda P, Kuske J, Savchynskyy B. 2017. A dual ascent framework for Lagrangean decomposition of combinatorial problems. CVPR: Computer Vision and Pattern Recognition vol. 2017. 4950–4960.
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2017 | Conference Paper | IST-REx-ID: 641
Trajkovska V, Swoboda P, Åström F, Petra S. 2017. Graphical model parameter learning by inverse linear programming. SSVM: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 10302. 323–334.
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2017 | Conference Paper | IST-REx-ID: 646   OA
Kuske J, Swoboda P, Petra S. 2017. A novel convex relaxation for non binary discrete tomography. SSVM: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 10302. 235–246.
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