{"project":[{"grant_number":"616160","_id":"25FBA906-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Discrete Optimization in Computer Vision: Theory and Practice"}],"publication_status":"published","month":"06","scopus_import":"1","oa_version":"Preprint","article_number":"11138-11147","publication_identifier":{"issn":["10636919"],"isbn":["9781728132938"]},"year":"2019","volume":"2019-June","language":[{"iso":"eng"}],"conference":{"name":"CVPR: Conference on Computer Vision and Pattern Recognition","start_date":"2019-06-15","location":"Long Beach, CA, United States","end_date":"2019-06-20"},"date_created":"2020-02-09T23:00:52Z","date_updated":"2023-09-07T14:54:24Z","author":[{"id":"446560C6-F248-11E8-B48F-1D18A9856A87","full_name":"Swoboda, Paul","last_name":"Swoboda","first_name":"Paul"},{"id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","first_name":"Vladimir","full_name":"Kolmogorov, Vladimir","last_name":"Kolmogorov"}],"publication":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","department":[{"_id":"VlKo"}],"_id":"7468","status":"public","date_published":"2019-06-01T00:00:00Z","external_id":{"isi":["000542649304076"],"arxiv":["1806.05049"]},"ec_funded":1,"doi":"10.1109/CVPR.2019.01140","article_processing_charge":"No","citation":{"apa":"Swoboda, P., &#38; Kolmogorov, V. (2019). Map inference via block-coordinate Frank-Wolfe algorithm. In <i>Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition</i> (Vol. 2019–June). Long Beach, CA, United States: IEEE. <a href=\"https://doi.org/10.1109/CVPR.2019.01140\">https://doi.org/10.1109/CVPR.2019.01140</a>","chicago":"Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” In <i>Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition</i>, Vol. 2019–June. IEEE, 2019. <a href=\"https://doi.org/10.1109/CVPR.2019.01140\">https://doi.org/10.1109/CVPR.2019.01140</a>.","ieee":"P. Swoboda and V. Kolmogorov, “Map inference via block-coordinate Frank-Wolfe algorithm,” in <i>Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition</i>, Long Beach, CA, United States, 2019, vol. 2019–June.","ama":"Swoboda P, Kolmogorov V. Map inference via block-coordinate Frank-Wolfe algorithm. In: <i>Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition</i>. Vol 2019-June. IEEE; 2019. doi:<a href=\"https://doi.org/10.1109/CVPR.2019.01140\">10.1109/CVPR.2019.01140</a>","short":"P. Swoboda, V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2019.","ista":"Swoboda P, Kolmogorov V. 2019. Map inference via block-coordinate Frank-Wolfe algorithm. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition vol. 2019–June, 11138–11147.","mla":"Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” <i>Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition</i>, vol. 2019–June, 11138–11147, IEEE, 2019, doi:<a href=\"https://doi.org/10.1109/CVPR.2019.01140\">10.1109/CVPR.2019.01140</a>."},"quality_controlled":"1","oa":1,"title":"Map inference via block-coordinate Frank-Wolfe algorithm","publisher":"IEEE","type":"conference","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","day":"01","main_file_link":[{"url":"https://arxiv.org/abs/1806.05049","open_access":"1"}],"abstract":[{"lang":"eng","text":"We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems. The method optimizes a Lagrangean relaxation of the original energy minimization problem using a multi plane block-coordinate Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean decomposition. We show empirically that our method outperforms state-of-the-art Lagrangean decomposition based algorithms on some challenging Markov Random Field, multi-label discrete tomography and graph matching problems."}],"isi":1}