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1. Verfasser: Trevisan, Chris
Format: Preprint
Veröffentlicht: 2023
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Online-Zugang:https://arxiv.org/abs/2310.09483
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author Trevisan, Chris
author_facet Trevisan, Chris
contents We continue the study of selection and sorting of $n$ numbers under the adversarial comparator model, where comparisons can be adversarially tampered with if the arguments are sufficiently close. We derive a randomized sorting algorithm that does $O(n \log^2 n)$ comparisons and gives a correct answer with high probability, addressing an open problem of Ajtai, Feldman, Hassadim, and Nelson [AFHN15]. Our algorithm also implies a selection algorithm that does $O(n \log n)$ comparisons and gives a correct answer with high probability. Both of these results are a $\log$ factor away from the naive lower bound. [AFHN15] shows an $Ω(n^{1+\varepsilon})$ lower bound for both sorting and selection in the deterministic case, so our results also prove a discrepancy between what is possible with deterministic and randomized algorithms in this setting. We also consider both sorting and selection in rounds, exploring the tradeoff between accuracy, number of comparisons, and number of rounds. Using results from sorting networks, we give general algorithms for sorting in $d$ rounds where the number of comparisons increases with $d$ and the accuracy decreases with $d$. Using these algorithms, we derive selection algorithms in $d+O(\log d)$ rounds that use the same number of comparisons as the corresponding sorting algorithm, but have a constant accuracy. Notably, this gives selection algorithms in $d$ rounds that use $n^{1 + o(1)}$ comparisons and have constant accuracy for all $d = ω(1)$, which still beats the deterministic lower bound of $Ω(n^{1+\varepsilon})$.
format Preprint
id arxiv_https___arxiv_org_abs_2310_09483
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Sorting and Selection in Rounds with Adversarial Comparisons
Trevisan, Chris
Data Structures and Algorithms
We continue the study of selection and sorting of $n$ numbers under the adversarial comparator model, where comparisons can be adversarially tampered with if the arguments are sufficiently close. We derive a randomized sorting algorithm that does $O(n \log^2 n)$ comparisons and gives a correct answer with high probability, addressing an open problem of Ajtai, Feldman, Hassadim, and Nelson [AFHN15]. Our algorithm also implies a selection algorithm that does $O(n \log n)$ comparisons and gives a correct answer with high probability. Both of these results are a $\log$ factor away from the naive lower bound. [AFHN15] shows an $Ω(n^{1+\varepsilon})$ lower bound for both sorting and selection in the deterministic case, so our results also prove a discrepancy between what is possible with deterministic and randomized algorithms in this setting. We also consider both sorting and selection in rounds, exploring the tradeoff between accuracy, number of comparisons, and number of rounds. Using results from sorting networks, we give general algorithms for sorting in $d$ rounds where the number of comparisons increases with $d$ and the accuracy decreases with $d$. Using these algorithms, we derive selection algorithms in $d+O(\log d)$ rounds that use the same number of comparisons as the corresponding sorting algorithm, but have a constant accuracy. Notably, this gives selection algorithms in $d$ rounds that use $n^{1 + o(1)}$ comparisons and have constant accuracy for all $d = ω(1)$, which still beats the deterministic lower bound of $Ω(n^{1+\varepsilon})$.
title Sorting and Selection in Rounds with Adversarial Comparisons
topic Data Structures and Algorithms
url https://arxiv.org/abs/2310.09483