{"scopus_import":1,"date_created":"2018-12-11T11:54:18Z","status":"public","day":"01","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","_id":"1841","page":"919 - 930","language":[{"iso":"eng"}],"oa_version":"Preprint","author":[{"last_name":"Kolmogorov","full_name":"Kolmogorov, Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","first_name":"Vladimir"}],"publisher":"IEEE","publication_status":"published","date_published":"2015-05-01T00:00:00Z","month":"05","publist_id":"5261","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1309.5655"}],"ec_funded":1,"date_updated":"2021-01-12T06:53:33Z","citation":{"mla":"Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 5, IEEE, 2015, pp. 919–30, doi:<a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">10.1109/TPAMI.2014.2363465</a>.","short":"V. Kolmogorov, IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2015) 919–930.","ista":"Kolmogorov V. 2015. A new look at reweighted message passing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(5), 919–930.","chicago":"Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2015. <a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">https://doi.org/10.1109/TPAMI.2014.2363465</a>.","ama":"Kolmogorov V. A new look at reweighted message passing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2015;37(5):919-930. doi:<a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">10.1109/TPAMI.2014.2363465</a>","ieee":"V. Kolmogorov, “A new look at reweighted message passing,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 37, no. 5. IEEE, pp. 919–930, 2015.","apa":"Kolmogorov, V. (2015). A new look at reweighted message passing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/TPAMI.2014.2363465\">https://doi.org/10.1109/TPAMI.2014.2363465</a>"},"doi":"10.1109/TPAMI.2014.2363465","project":[{"call_identifier":"FP7","name":"Discrete Optimization in Computer Vision: Theory and Practice","grant_number":"616160","_id":"25FBA906-B435-11E9-9278-68D0E5697425"}],"type":"journal_article","intvolume":"        37","title":"A new look at reweighted message passing","department":[{"_id":"VlKo"}],"year":"2015","issue":"5","abstract":[{"text":"We propose a new family of message passing techniques for MAP estimation in graphical models which we call Sequential Reweighted Message Passing (SRMP). Special cases include well-known techniques such as Min-Sum Diffusion (MSD) and a faster Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation is simpler than the original derivation of TRW-S, and does not involve a decomposition into trees. This allows easy generalizations. The new family of algorithms can be viewed as a generalization of TRW-S from pairwise to higher-order graphical models. We test SRMP on several real-world problems with promising results.","lang":"eng"}],"quality_controlled":"1","oa":1,"volume":37,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"}