English

Randomized block Krylov method for approximation of truncated tensor SVD

Numerical Analysis 2026-03-25 v3 Numerical Analysis

Abstract

This paper is devoted to studying the application of the block Krylov subspace method for approximation of the truncated tensor SVD (T-SVD). The theoretical results of the proposed randomized approach are presented. Several experimental experiments using synthetics and real-world data are conducted to verify the efficiency and feasibility of the proposed randomized approach, and the numerical results show that the proposed method provides promising results. Applications of the proposed approach to data completion and data compression are presented.

Keywords

Cite

@article{arxiv.2504.04989,
  title  = {Randomized block Krylov method for approximation of truncated tensor SVD},
  author = {Malihe Nobakht Kooshkghazi and Salman Ahmadi-Asl and Andre L. F. de Almeida},
  journal= {arXiv preprint arXiv:2504.04989},
  year   = {2026}
}
R2 v1 2026-06-28T22:49:18.138Z