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.
Please cite this work as:
@article{shcherbakova2025fast,
title={Fast Computation of Eigenvector Centralities for Multilayer Networks with Nonnegative Tensor Train},
author={Shcherbakova, Elena M. and Tudisco, Francesco and Tyrtyshnikov, Eugene E.},
journal={Lobachevskii Journal of Mathematics},
volume={46},
number={8},
pages={3804--3814},
year={2025},
publisher={Springer}
}