Zobrazeno 1 - 10
of 2 785
pro vyhledávání: '"Briend, A."'
In this note we analyze the performance of a simple root-finding algorithm in uniform attachment trees. The leaf-stripping algorithm recursively removes all leaves of the tree for a carefully chosen number of rounds. We show that, with probability $1
Externí odkaz:
http://arxiv.org/abs/2410.06481
Autor:
Berry, Louigi Addario, Briend, Simon, Devroye, Luc, Donderwinkel, Serte, Kerriou, Céline, Lugosi, Gábor
We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saram\"aki and Kaski. Vertices are attached in a sequential manner one by one by selecting an existing target vertex and connecting
Externí odkaz:
http://arxiv.org/abs/2403.20185
This paper studies the problem of estimating the order of arrival of the vertices in a random recursive tree. Specifically, we study two fundamental models: the uniform attachment model and the linear preferential attachment model. We propose an orde
Externí odkaz:
http://arxiv.org/abs/2403.09755
Tukey's depth (or halfspace depth) is a widely used measure of centrality for multivariate data. However, exact computation of Tukey's depth is known to be a hard problem in high dimensions. As a remedy, randomized approximations of Tukey's depth hav
Externí odkaz:
http://arxiv.org/abs/2309.05657
Autor:
Damalie Nalwanga, Victor Musiime, Sarah Kiguli, Peter Olupot-Olupot, Florence Alaroker, Robert Opoka, Abner Tagoola, Hellen Mnjalla, Christabel Mogaka, Eva Nabawanuka, Elisa Giallongo, Charles Karamagi, André Briend, Kathryn Maitland
Publikováno v:
BMC Nutrition, Vol 10, Iss 1, Pp 1-9 (2024)
Abstract Background Pneumonia remains the leading cause of mortality among children under 5 years. Poor nutritional status increases pneumonia mortality. Nutritional status assessed by anthropometry alone does not provide information on which body co
Externí odkaz:
https://doaj.org/article/ab8375893a1c44ca9e4c1c5b6b8ea65e
A uniform $k$-{\sc dag} generalizes the uniform random recursive tree by picking $k$ parents uniformly at random from the existing nodes. It starts with $k$ ''roots''. Each of the $k$ roots is assigned a bit. These bits are propagated by a noisy chan
Externí odkaz:
http://arxiv.org/abs/2306.01727
Autor:
Louis-Hippolyte Minvielle Moncla, Mewen Briend, Mame Sokhna Sylla, Samuel Mathieu, Anne Rufiange, Yohan Bossé, Patrick Mathieu
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-15 (2024)
Abstract Background Mitral valve prolapse (MVP) is a common heart disorder characterized by an excessive production of proteoglycans and extracellular matrix in mitral valve leaflets. Large-scale genome-wide association study (GWAS) underlined that M
Externí odkaz:
https://doaj.org/article/ae65eb5cd17a41fb9304cc909e7de50f
Publikováno v:
Translational Psychiatry, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Human connectome studies have provided abundant data consistent with the hypothesis that functional dysconnectivity is predominant in psychosis spectrum disorders. Converging lines of evidence also suggest an interaction between dorsal anter
Externí odkaz:
https://doaj.org/article/3b8f592247744441aec4e295a159e50c
Autor:
Sébastien Thériault, Zhonglin Li, Erik Abner, Jian’an Luan, Hasanga D. Manikpurage, Ursula Houessou, Pardis Zamani, Mewen Briend, Estonian Biobank Research Team, Dominique K. Boudreau, Nathalie Gaudreault, Lily Frenette, Déborah Argaud, Manel Dahmene, François Dagenais, Marie-Annick Clavel, Philippe Pibarot, Benoit J. Arsenault, S. Matthijs Boekholdt, Nicholas J. Wareham, Tõnu Esko, Patrick Mathieu, Yohan Bossé
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract There is currently no medical therapy to prevent calcific aortic valve stenosis (CAVS). Multi-omics approaches could lead to the identification of novel molecular targets. Here, we perform a genome-wide association study (GWAS) meta-analysis
Externí odkaz:
https://doaj.org/article/5660b9921e9f456da6aee9115481bb7c
We study the problem of finding the root vertex in large growing networks. We prove that it is possible to construct confidence sets of size independent of the number of vertices in the network that contain the root vertex with high probability in va
Externí odkaz:
http://arxiv.org/abs/2207.14601