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Autori principali: Addario-Berry, Louigi, Fontaine, Catherine, Khanfir, Robin, Langevin, Louis-Roy, Têtu, Simone
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2411.18614
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author Addario-Berry, Louigi
Fontaine, Catherine
Khanfir, Robin
Langevin, Louis-Roy
Têtu, Simone
author_facet Addario-Berry, Louigi
Fontaine, Catherine
Khanfir, Robin
Langevin, Louis-Roy
Têtu, Simone
contents We consider root-finding algorithms for random rooted trees grown by uniform attachment. Given an unlabeled copy of the tree and a target accuracy $\varepsilon > 0$, such an algorithm outputs a set of nodes that contains the root with probability at least $1 - \varepsilon$. We prove that, for the optimal algorithm, an output set of size $\exp(O(\log^{1/2}(1/\varepsilon)))$ suffices; this bound is sharp and answers a question of Bubeck, Devroye and Lugosi (2017). We prove similar bounds for random regular trees that grow by uniform attachment, strengthening a result of Khim and Loh (2017).
format Preprint
id arxiv_https___arxiv_org_abs_2411_18614
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal root recovery for uniform attachment trees and $d$-regular growing trees
Addario-Berry, Louigi
Fontaine, Catherine
Khanfir, Robin
Langevin, Louis-Roy
Têtu, Simone
Data Structures and Algorithms
Social and Information Networks
Probability
Statistics Theory
60C05, 05C80, 62M05, 94C15
We consider root-finding algorithms for random rooted trees grown by uniform attachment. Given an unlabeled copy of the tree and a target accuracy $\varepsilon > 0$, such an algorithm outputs a set of nodes that contains the root with probability at least $1 - \varepsilon$. We prove that, for the optimal algorithm, an output set of size $\exp(O(\log^{1/2}(1/\varepsilon)))$ suffices; this bound is sharp and answers a question of Bubeck, Devroye and Lugosi (2017). We prove similar bounds for random regular trees that grow by uniform attachment, strengthening a result of Khim and Loh (2017).
title Optimal root recovery for uniform attachment trees and $d$-regular growing trees
topic Data Structures and Algorithms
Social and Information Networks
Probability
Statistics Theory
60C05, 05C80, 62M05, 94C15
url https://arxiv.org/abs/2411.18614