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Abstract <p>In this article, we introduce eigenvector centralities for higher-order multilayer networks and suggest to use nonnegative tensor train decomposition for fast computations of dominant eigenvectors of multi-homogeneous maps via power iterates. The analysis of the approximation error for using nonnegative tensor train instead of the original nonnegative tensor is presented.</p>

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Fast Computation of Eigenvector Centralities for Multilayer Networks with Nonnegative Tensor Train

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • E. M. Shcherbakova,
  • F. Tudisco,
  • E. E. Tyrtyshnikov

摘要

Abstract

In this article, we introduce eigenvector centralities for higher-order multilayer networks and suggest to use nonnegative tensor train decomposition for fast computations of dominant eigenvectors of multi-homogeneous maps via power iterates. The analysis of the approximation error for using nonnegative tensor train instead of the original nonnegative tensor is presented.