{"date_created":"2020-02-09T23:00:52Z","language":[{"iso":"eng"}],"article_processing_charge":"No","article_number":"11138-11147","conference":{"start_date":"2019-06-15","name":"CVPR: Conference on Computer Vision and Pattern Recognition","location":"Long Beach, CA, United States","end_date":"2019-06-20"},"date_published":"2019-06-01T00:00:00Z","publisher":"IEEE","quality_controlled":"1","main_file_link":[{"url":"https://arxiv.org/abs/1806.05049","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","department":[{"_id":"VlKo"}],"oa":1,"volume":"2019-June","year":"2019","oa_version":"Preprint","author":[{"last_name":"Swoboda","first_name":"Paul","id":"446560C6-F248-11E8-B48F-1D18A9856A87","full_name":"Swoboda, Paul"},{"full_name":"Kolmogorov, Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","first_name":"Vladimir","last_name":"Kolmogorov"}],"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."}],"citation":{"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.","apa":"Swoboda, P., & Kolmogorov, V. (2019). Map inference via block-coordinate Frank-Wolfe algorithm. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2019–June). Long Beach, CA, United States: IEEE. https://doi.org/10.1109/CVPR.2019.01140","short":"P. Swoboda, V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2019.","ieee":"P. Swoboda and V. Kolmogorov, “Map inference via block-coordinate Frank-Wolfe algorithm,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Beach, CA, United States, 2019, vol. 2019–June.","chicago":"Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2019–June. IEEE, 2019. https://doi.org/10.1109/CVPR.2019.01140.","mla":"Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2019–June, 11138–11147, IEEE, 2019, doi:10.1109/CVPR.2019.01140.","ama":"Swoboda P, Kolmogorov V. Map inference via block-coordinate Frank-Wolfe algorithm. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol 2019-June. IEEE; 2019. doi:10.1109/CVPR.2019.01140"},"month":"06","title":"Map inference via block-coordinate Frank-Wolfe algorithm","type":"conference","external_id":{"arxiv":["1806.05049"]},"status":"public","ec_funded":1,"day":"01","publication_identifier":{"issn":["10636919"],"isbn":["9781728132938"]},"doi":"10.1109/CVPR.2019.01140","scopus_import":1,"publication":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","date_updated":"2021-01-12T08:13:45Z","project":[{"_id":"25FBA906-B435-11E9-9278-68D0E5697425","grant_number":"616160","call_identifier":"FP7","name":"Discrete Optimization in Computer Vision: Theory and Practice"}],"_id":"7468"}