2026-08-15T11:11:19Z https://drops.dagstuhl.de/oai

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Extensions of Self-Improving Sorters Cheng, Siu-Wing Yan, Lie sorting self-improving algorithms entropy Ailon et al. (SICOMP 2011) proposed a self-improving sorter that tunes its performance to the unknown input distribution in a training phase. The distribution of the input numbers x_1,x_2,...,x_n must be of the product type, that is, each x_i is drawn independently from an arbitrary distribution D_i, and the D_i's are independent of each other. We study two extensions that relax this requirement. The first extension models hidden classes in the input. We consider the case that numbers in the same class are governed by linear functions of the same hidden random parameter. The second extension considers a hidden mixture of product distributions. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Siu-Wing Cheng and Lie Yan 2018 Is Part Of LIPIcs, Volume 123, 29th International Symposium on Algorithms and Computation (ISAAC 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ISAAC.2018.63 urn:nbn:de:0030-drops-100111 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2018.63 eng https://creativecommons.org/licenses/by/3.0/legalcode