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  4. Optimal sorting with persistent comparison errors
 
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Optimal sorting with persistent comparison errors

Journal
Leibniz International Proceedings in Informatics, LIPIcs
Journal Volume
144
Date Issued
2019
Author(s)
Geissmann B
Leucci S
Liu C.-H
Penna P.
CHIH-HUNG LIU  
DOI
10.4230/LIPIcs.ESA.2019.49
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074868778&doi=10.4230%2fLIPIcs.ESA.2019.49&partnerID=40&md5=cec2da9b07470af580c193032565e2b0
https://scholars.lib.ntu.edu.tw/handle/123456789/624634
Abstract
We consider the problem of sorting n elements in the case of persistent comparison errors. In this problem, each comparison between two elements can be wrong with some fixed (small) probability p, and comparisons cannot be repeated (Braverman and Mossel, SODA’08). Sorting perfectly in this model is impossible, and the objective is to minimize the dislocation of each element in the output sequence, that is, the difference between its true rank and its position. Existing lower bounds for this problem show that no algorithm can guarantee, with high probability, maximum dislocation and total dislocation better than Ω(log n) and Ω(n), respectively, regardless of its running time. In this paper, we present the first O(n log n)-time sorting algorithm that guarantees both O(log n) maximum dislocation and O(n) total dislocation with high probability. This settles the time complexity of this problem and shows that comparison errors do not increase its computational difficulty: a sequence with the best possible dislocation can be obtained in O(n log n) time and, even without comparison errors, Ω(n log n) time is necessary to guarantee such dislocation bounds. In order to achieve this optimality result, we solve two sub-problems in the persistent error comparisons model, and the respective methods have their own merits for further application. One is how to locate a position in which to insert an element in an almost-sorted sequence having O(log n) maximum dislocation in such a way that the dislocation of the resulting sequence will still be O(log n). The other is how to simultaneously insert m elements into an almost sorted sequence of m different elements, such that the resulting sequence of 2m elements remains almost sorted. © Barbara Geissmann, Stefano Leucci, Chih-Hung Liu, and Paolo Penna.
Subjects
Approximate sorting; Comparison errors; Persistent errors
Other Subjects
Probability; High probability; Lower bounds; Optimal sorting; Output sequences; Persistent errors; Probability p; Sorting algorithm; Time complexity; Errors
Type
conference paper

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