dc.creatorBracht E.C.
dc.creatorMeira L.A.A.
dc.creatorMiyazawa F.K.
dc.date2004
dc.date2015-06-26T14:23:49Z
dc.date2015-11-26T14:12:10Z
dc.date2015-06-26T14:23:49Z
dc.date2015-11-26T14:12:10Z
dc.date.accessioned2018-03-28T21:12:46Z
dc.date.available2018-03-28T21:12:46Z
dc.identifier
dc.identifierLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). , v. 3059, n. , p. 145 - 158, 2004.
dc.identifier3029743
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-35048821065&partnerID=40&md5=d5e7d6af18f45c5155ec16faff2801f5
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/94262
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/94262
dc.identifier2-s2.0-35048821065
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1241923
dc.descriptionIn this paper we present a new fast approximation algorithm for the Uniform Metric Labeling Problem. This is an important classification problem that occur in many applications which consider the assignment of objects into labels, in a way that is consistent with some observed data that includes the relationship between the objects. The known approximation algorithms are based on solutions of large linear programs and are impractical for moderated and large size instances. We present an 8 log n-approximation algorithm analyzed by a primal-dual technique which, although has factor greater than the previous algorithms, can be applied to large sized instances. We obtained experimental results on computational generated and image processing instances with the new algorithm and two others LP-based approximation algorithms. For these instances our algorithm present a considerable gain of computational time and the error ratio, when possible to compare, was less than 2% from the optimum. © Springer-Verlag 2004.
dc.description3059
dc.description
dc.description145
dc.description158
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dc.languageen
dc.publisher
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsfechado
dc.sourceScopus
dc.titleA Greedy Approximation Algorithm For The Uniform Labeling Problem Analyzed By A Primal-dual Technique
dc.typeArtículos de revistas


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