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60 Publications

2018 | Conference Paper | IST-REx-ID: 273 | OA
Mohapatra, P., Rolinek, M., Jawahar, C. V., Kolmogorov, V., & Kumar, M. P. (2018). Efficient optimization for rank-based loss functions. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3693–3701). Salt Lake City, UT, USA: IEEE. https://doi.org/10.1109/cvpr.2018.00389
View | DOI | Download Preprint (ext.) | arXiv
 
2018 | Journal Article | IST-REx-ID: 703 | OA
Shekhovtsov, A., Swoboda, P., & Savchynskyy, B. (2018). Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(7), 1668–1682. https://doi.org/10.1109/TPAMI.2017.2730884
View | DOI | Download Preprint (ext.) | arXiv
 
2018 | Journal Article | IST-REx-ID: 18 | OA
Kolmogorov, V., & Rolinek, M. (2018). Superconcentrators of density 25.3. Ars Combinatoria, 141(10), 269–304.
View | Download Preprint (ext.) | arXiv
 
2018 | Conference Paper | IST-REx-ID: 193 | OA
Alwen, J. F., Gazi, P., Kamath Hosdurg, C., Klein, K., Osang, G. F., Pietrzak, K. Z., … Rybar, M. (2018). On the memory hardness of data independent password hashing functions. In Proceedings of the 2018 on Asia Conference on Computer and Communication Security (pp. 51–65). Incheon, Republic of Korea: ACM. https://doi.org/10.1145/3196494.3196534
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2018 | Conference Paper | IST-REx-ID: 5978 | OA
Haller, S., Swoboda, P., & Savchynskyy, B. (2018). Exact MAP-inference by confining combinatorial search with LP relaxation. In Proceedings of the 32st AAAI Conference on Artificial Intelligence (pp. 6581–6588). New Orleans, LU, United States: AAAI.
View | Download Preprint (ext.) | arXiv
 
2017 | Research Data | IST-REx-ID: 5561 | OA
Kainmueller, D., Jug, F., Rother, C., & Meyers, G. (2017). Graph matching problems for annotating C. Elegans. IST Austria. https://doi.org/10.15479/AT:ISTA:57
View | Files available | DOI
 
2017 | Conference Paper | IST-REx-ID: 274 | OA
Kolmogorov, V. (2017). A faster approximation algorithm for the Gibbs partition function. In Proceedings of the 31st Conference On Learning Theory (Vol. 75, pp. 228–249). PMLR.
View | Files available | arXiv
 
2017 | Conference Paper | IST-REx-ID: 641
Trajkovska, V., Swoboda, P., Åström, F., & Petra, S. (2017). Graphical model parameter learning by inverse linear programming. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 323–334). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_26
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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. https://doi.org/10.1137/16M1091836
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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. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 235–246). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_19
View | DOI | Download Submitted Version (ext.)
 

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