{"volume":2017,"publist_id":"6524","intvolume":"      2017","year":"2017","isi":1,"file_date_updated":"2020-07-14T12:48:15Z","ddc":["000"],"project":[{"call_identifier":"FP7","_id":"25FBA906-B435-11E9-9278-68D0E5697425","name":"Discrete Optimization in Computer Vision: Theory and Practice","grant_number":"616160"}],"doi":"10.1109/CVPR.2017.526","page":"4950-4960","author":[{"full_name":"Swoboda, Paul","id":"446560C6-F248-11E8-B48F-1D18A9856A87","last_name":"Swoboda","first_name":"Paul"},{"full_name":"Kuske, Jan","first_name":"Jan","last_name":"Kuske"},{"first_name":"Bogdan","last_name":"Savchynskyy","full_name":"Savchynskyy, Bogdan"}],"has_accepted_license":"1","publication_identifier":{"isbn":["978-153860457-1"]},"external_id":{"isi":["000418371405005"]},"ec_funded":1,"citation":{"short":"P. Swoboda, J. Kuske, B. Savchynskyy, in:, IEEE, 2017, pp. 4950–4960.","chicago":"Swoboda, Paul, Jan Kuske, and Bogdan Savchynskyy. “A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems,” 2017:4950–60. IEEE, 2017. <a href=\"https://doi.org/10.1109/CVPR.2017.526\">https://doi.org/10.1109/CVPR.2017.526</a>.","ista":"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.","apa":"Swoboda, P., Kuske, J., &#38; Savchynskyy, B. (2017). A dual ascent framework for Lagrangean decomposition of combinatorial problems (Vol. 2017, pp. 4950–4960). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. <a href=\"https://doi.org/10.1109/CVPR.2017.526\">https://doi.org/10.1109/CVPR.2017.526</a>","ama":"Swoboda P, Kuske J, Savchynskyy B. A dual ascent framework for Lagrangean decomposition of combinatorial problems. In: Vol 2017. IEEE; 2017:4950-4960. doi:<a href=\"https://doi.org/10.1109/CVPR.2017.526\">10.1109/CVPR.2017.526</a>","ieee":"P. Swoboda, J. Kuske, and B. Savchynskyy, “A dual ascent framework for Lagrangean decomposition of combinatorial problems,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 4950–4960.","mla":"Swoboda, Paul, et al. <i>A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems</i>. Vol. 2017, IEEE, 2017, pp. 4950–60, doi:<a href=\"https://doi.org/10.1109/CVPR.2017.526\">10.1109/CVPR.2017.526</a>."},"conference":{"start_date":"2017-07-21","name":"CVPR: Computer Vision and Pattern Recognition","end_date":"2017-07-26","location":"Honolulu, HA, United States"},"language":[{"iso":"eng"}],"_id":"917","date_created":"2018-12-11T11:49:11Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa":1,"oa_version":"Submitted Version","scopus_import":"1","publisher":"IEEE","status":"public","quality_controlled":"1","title":"A dual ascent framework for Lagrangean decomposition of combinatorial problems","day":"01","file":[{"relation":"main_file","checksum":"72fd291046bd8e5717961bd68f6b6f03","content_type":"application/pdf","file_name":"2017_CVPR_Swoboda.pdf","creator":"dernst","access_level":"open_access","date_updated":"2020-07-14T12:48:15Z","file_id":"5847","date_created":"2019-01-18T12:45:55Z","file_size":898652}],"type":"conference","date_updated":"2023-09-26T15:41:11Z","article_processing_charge":"No","month":"07","date_published":"2017-07-01T00:00:00Z","publication_status":"published","abstract":[{"text":"We  propose  a  general  dual  ascent  framework  for  Lagrangean decomposition of combinatorial problems.  Although methods of this type have shown their efficiency for a number of problems, so far there was no general algorithm applicable to multiple problem types. In this work, we propose such a general algorithm. It depends on several parameters, which can be used to optimize its performance in each particular setting. We demonstrate efficacy of our method on graph matching and multicut problems, where it outperforms state-of-the-art solvers including those based on subgradient optimization and off-the-shelf linear programming solvers.","lang":"eng"}],"department":[{"_id":"VlKo"}]}