{"month":"09","date_updated":"2019-01-24T13:07:32Z","author":[{"first_name":"Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","last_name":"Kolmogorov","full_name":"Vladimir Kolmogorov"}],"title":"Reweighted message passing revisited","_id":"2273","citation":{"apa":"Kolmogorov, V. (2013). <i>Reweighted message passing revisited</i>. IST Austria.","chicago":"Kolmogorov, Vladimir. <i>Reweighted Message Passing Revisited</i>. IST Austria, 2013.","mla":"Kolmogorov, Vladimir. <i>Reweighted Message Passing Revisited</i>. IST Austria, 2013.","ieee":"V. Kolmogorov, <i>Reweighted message passing revisited</i>. IST Austria, 2013.","ama":"Kolmogorov V. <i>Reweighted Message Passing Revisited</i>. IST Austria; 2013.","ista":"Kolmogorov V. 2013. Reweighted message passing revisited, IST Austria,p.","short":"V. Kolmogorov, Reweighted Message Passing Revisited, IST Austria, 2013."},"type":"report","date_published":"2013-09-22T00:00:00Z","date_created":"2018-12-11T11:56:42Z","publication_status":"published","day":"22","status":"public","extern":0,"department":[{"_id":"VlKo"}],"oa":1,"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 Diusion (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. We present such a generalization for the case of higher-order graphical models, and test it on several real-world problems with promising results.","lang":"eng"}],"year":"2013","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1309.5655"}],"publist_id":"4671","quality_controlled":0,"publisher":"IST Austria"}