Results 161 to 170 of about 744,531 (188)
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Journal of Algorithms, 1983
Abstract Dans cet article, nous proposons un algorithme de complexite polynomiale pour construire un arbre au hasard qui soit un graphe partiel d'un graphe donne. Il consiste essentielleement a construire une arborescence de rang donne sur ce graphe, l'ensemble des arborescences etant ordonne par rapport aux valeurs croissantes de la racine et a ...
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Abstract Dans cet article, nous proposons un algorithme de complexite polynomiale pour construire un arbre au hasard qui soit un graphe partiel d'un graphe donne. Il consiste essentielleement a construire une arborescence de rang donne sur ce graphe, l'ensemble des arborescences etant ordonne par rapport aux valeurs croissantes de la racine et a ...
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Studia Scientiarum Mathematicarum Hungarica, 2002
In a one-parameter model for evolution of random trees strong law of large numbers and central limit theorem are proved for the number of vertices with low degree. The proof is based on elementary martingale theory.
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In a one-parameter model for evolution of random trees strong law of large numbers and central limit theorem are proved for the number of vertices with low degree. The proof is based on elementary martingale theory.
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1972
A random tree is a probabilistic system much like a random walk. In a random walk, a particle moves up or down as time progresses in accordance with some stochastic law. A random tree, on the other hand, starts with one particle at time zero, this particle branches into a number of particles, each of which move up or down in accordance with a ...
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A random tree is a probabilistic system much like a random walk. In a random walk, a particle moves up or down as time progresses in accordance with some stochastic law. A random tree, on the other hand, starts with one particle at time zero, this particle branches into a number of particles, each of which move up or down in accordance with a ...
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1992
In this lecture we will describe a very simple probabilistic data structure that allows inserts, deletes, and membership tests (among other operations) in expected logarithmic time.
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In this lecture we will describe a very simple probabilistic data structure that allows inserts, deletes, and membership tests (among other operations) in expected logarithmic time.
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Noble-Metal Based Random Alloy and Intermetallic Nanocrystals: Syntheses and Applications
Chemical Reviews, 2021Ming Zhou, Can Li, Jiye Fang
exaly
Computational advantage of quantum random sampling
Reviews of Modern Physics, 2023Dominik Hangleiter, Jens Eisert
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