| |  Online-Ressource |
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| Verfasst von: | Swoboda, Paul [VerfasserIn]  |
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| | Kappes, Jörg Hendrik [VerfasserIn] |
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| | Schnörr, Christoph [VerfasserIn] |
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| | Savchynskyy, Bogdan [VerfasserIn] |
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| Titel: | Partial optimality by pruning for MAP-inference with general graphical models |
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| Verf.angabe: | Paul Swoboda, Alexander Shekhovtsov, Jörg Hendrik Kappes, Christoph Schnörr, and Bogdan Savchynskyy |
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| Jahr: | 2016 |
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| Jahr des Originals: | 2015 |
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| Umfang: | 13 S. |
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| Fussnoten: | Date of publication 12 Oct 2015 ; Gesehen am 26.05.2020 |
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| Titel Quelle: | Enthalten in: Institute of Electrical and Electronics EngineersIEEE transactions on pattern analysis and machine intelligence |
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| Ort Quelle: | New York, NY : IEEE, 1979 |
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| Jahr Quelle: | 2016 |
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| Band/Heft Quelle: | 38(2016), 7, Seite 1370-1382 |
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| ISSN Quelle: | 1939-3539 |
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| Abstract: | We consider the energy minimization problem for undirected graphical models, also known as MAP-inference problem for Markov random fields which is NP-hard in general. We propose a novel polynomial time algorithm to obtain a part of its optimal non-relaxed integral solution. Our algorithm is initialized with variables taking integral values in the solution of a convex relaxation of the MAP-inference problem and iteratively prunes those, which do not satisfy our criterion for partial optimality. We show that our pruning strategy is in a certain sense theoretically optimal. Also empirically our method outperforms previous approaches in terms of the number of persistently labelled variables. The method is very general, as it is applicable to models with arbitrary factors of an arbitrary order and can employ any solver for the considered relaxed problem. Our method's runtime is determined by the runtime of the convex relaxation solver for the MAP-inference problem. |
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| DOI: | doi:10.1109/TPAMI.2015.2484327 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1109/TPAMI.2015.2484327 |
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| | DOI: https://doi.org/10.1109/TPAMI.2015.2484327 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | computational complexity |
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| | convex relaxation solver |
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| | directed graphs |
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| | energy minimization |
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| | energy minimization problem |
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| | general graphical models |
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| | Graphical models |
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| | inference mechanisms |
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| | Labeling |
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| | local polytope |
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| | MAP-inference |
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| | MAP-inference problem |
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| | Markov processes |
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| | Markov random fields |
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| | minimisation |
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| | Minimization |
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| | NP-hard problem |
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| | optimal nonrelaxed integral solution |
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| | partial optimality |
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| | persistency |
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| | polynomial time algorithm |
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| | Polynomials |
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| | pruning strategy |
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| | Runtime |
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| | Signal processing algorithms |
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| | undirected graphical models |
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| K10plus-PPN: | 1698831986 |
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| Verknüpfungen: | → Zeitschrift |
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Partial optimality by pruning for MAP-inference with general graphical models / Swoboda, Paul [VerfasserIn]; 2016 (Online-Ressource)
