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On the convergence rate and some applications of regularized ranking algorithms

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dc.contributor.author Kriukova, Galyna
dc.contributor.author Pereverzyev, Sergei V.
dc.contributor.author Tkachenko, Pavlo
dc.date.accessioned 2017-06-14T14:22:32Z
dc.date.available 2017-06-14T14:22:32Z
dc.date.issued 2016
dc.identifier.citation Kriukova Galyna. On the convergence rate and some applications of regularized ranking algorithms / Galyna Kriukova, Sergei V. Pereverzyev, Pavlo Tkachenko // Journal of Complexity. - 2016. - Vol. 33, April. - P. 14-29. uk
dc.identifier.uri http://ekmair.ukma.edu.ua/handle/123456789/11576
dc.identifier.uri http://dx.doi.org/10.1016/j.jco.2015.09.004 en
dc.description.abstract This paper studies the ranking problem in the context of the regularization theory that allows a simultaneous analysis of a wide class of ranking algorithms. Some of them were previously studied separately. For such ones, our analysis gives a better convergence rate compared to the reported in the literature. We also supplement our theoretical results with numerical illustrations and discuss the application of ranking to the problem of estimating the risk from errors in blood glucose measurements of diabetic patients. en
dc.language.iso en uk
dc.subject ranking en
dc.subject convergence rate en
dc.subject source condition en
dc.subject blood glucose error grid en
dc.title On the convergence rate and some applications of regularized ranking algorithms en
dc.type Article uk
dc.status published earlier uk
dc.relation.source Journal of Complexity uk


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