On the Escape Probability Estimation in Large Graphs

We consider the large graphs as the object of study and deal with the problem of escape probability estimation. Generally, the required characteristic cannot be calculated analytically and even numerically due to the complexity and large size of the investigation object. The purpose of this paper is...

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Main Authors: Konstantin Avrachenkov, Alexandra Borodina
Format: Article
Language:English
Published: FRUCT 2019-04-01
Series:Proceedings of the XXth Conference of Open Innovations Association FRUCT
Subjects:
Online Access:https://fruct.org/publications/fruct24/files/Avr.pdf
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author Konstantin Avrachenkov
Alexandra Borodina
author_facet Konstantin Avrachenkov
Alexandra Borodina
author_sort Konstantin Avrachenkov
collection DOAJ
description We consider the large graphs as the object of study and deal with the problem of escape probability estimation. Generally, the required characteristic cannot be calculated analytically and even numerically due to the complexity and large size of the investigation object. The purpose of this paper is to offer the effective method for estimating the probability that the random walk on graph фЂ‚їrst enters a node b before returning into starting node a. Regenerative properties of the random walk allow using an accelerated method for the cycles simulation based on the splitting technique. The results of numerical experiments confirm the advantages of the proposed method.
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spelling doaj.art-40be09f0d4854f068a3846735ca3b8cf2022-12-21T19:02:26ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372019-04-01854242430On the Escape Probability Estimation in Large GraphsKonstantin Avrachenkov0Alexandra Borodina1Inria, Sophia, Antipolis, FrancePetrozavodsk State University, Institute of Applied Mathematical Research of the Karelian Research Centre of RAS, Petrozavodsk, RussiaWe consider the large graphs as the object of study and deal with the problem of escape probability estimation. Generally, the required characteristic cannot be calculated analytically and even numerically due to the complexity and large size of the investigation object. The purpose of this paper is to offer the effective method for estimating the probability that the random walk on graph фЂ‚їrst enters a node b before returning into starting node a. Regenerative properties of the random walk allow using an accelerated method for the cycles simulation based on the splitting technique. The results of numerical experiments confirm the advantages of the proposed method.https://fruct.org/publications/fruct24/files/Avr.pdf escape probabilitylarge graphsMonte Carlo methodregenerative simulationsplitting method
spellingShingle Konstantin Avrachenkov
Alexandra Borodina
On the Escape Probability Estimation in Large Graphs
Proceedings of the XXth Conference of Open Innovations Association FRUCT
escape probability
large graphs
Monte Carlo method
regenerative simulation
splitting method
title On the Escape Probability Estimation in Large Graphs
title_full On the Escape Probability Estimation in Large Graphs
title_fullStr On the Escape Probability Estimation in Large Graphs
title_full_unstemmed On the Escape Probability Estimation in Large Graphs
title_short On the Escape Probability Estimation in Large Graphs
title_sort on the escape probability estimation in large graphs
topic escape probability
large graphs
Monte Carlo method
regenerative simulation
splitting method
url https://fruct.org/publications/fruct24/files/Avr.pdf
work_keys_str_mv AT konstantinavrachenkov ontheescapeprobabilityestimationinlargegraphs
AT alexandraborodina ontheescapeprobabilityestimationinlargegraphs