Regularization-based solution of the PageRank problem for large matrices

DOI10.1134/S0005117912110094zbMath1268.93014OpenAlexW2047368133MaRDI QIDQ2393054

A. A. Tremba, Boris T. Polyak

Publication date: 7 August 2013

Published in: Automation and Remote Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0005117912110094

zbMATH Keywords

column-stochastic matrixpagerank of web pagesregularization-based solution

Mathematics Subject Classification ID

Eigenvalue problems (93B60) Stochastic systems in control theory (general) (93E03) Large-scale systems (93A15)

Related Items (5)

Models of latent consensus ⋮ Efficient numerical methods to solve sparse linear equations with application to PageRank ⋮ On the role of the eigenprojector of the Laplacian matrix for reaching consensus in multiagent second-order systems ⋮ Saddle point mirror descent algorithm for the robust PageRank problem ⋮ On efficient randomized algorithms for finding the PageRank vector

Uses Software

• WebGraph

Cites Work

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• The projection method for reaching consensus and the regularized power limit of a stochastic matrix
• The $25,000,000,000 Eigenvector: The Linear Algebra behind Google
• Matrix Analysis
• Distribution of PageRank Mass Among Principle Components of the Web

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