English

Stochastic Trace and Diagonal Estimator for Tensors

Numerical Analysis 2025-10-28 v1 Numerical Analysis Statistics Theory Statistics Theory

Abstract

We consider the problem of estimating the trace and diagonal entries of an N-order tensor (where N2N \geq 2) under the framework where the tensor can only be accessed through tensor-vector multiplication. The aim is to estimate the tensor's diagonal entries and trace by minimizing the number of tensor-vector queries. The seminal work of Hutchinson and its extended version due to Bekas et al. give unbiased estimates of the trace and diagonal elements of a given matrix, respectively, using matrix-vector queries. However, to the best of our knowledge, no analogous results are known for estimating the trace and diagonal entries of higher-order tensors using tensor-vector queries. This paper addresses this gap and presents unbiased estimators for the trace and diagonal entries of a tensor under this model. Our proposed methods can be seen as generalizations of Hutchinson's and Bekas et al.'s estimators and reduce to their estimators when N = 2. We provide a rigorous theoretical analysis of our proposals and complement it with supporting simulations.

Keywords

Cite

@article{arxiv.2510.22157,
  title  = {Stochastic Trace and Diagonal Estimator for Tensors},
  author = {Bhisham Dev Verma and Rameshwar Pratap and Keegan Kang},
  journal= {arXiv preprint arXiv:2510.22157},
  year   = {2025}
}

Comments

29 pages and 5 figures

R2 v1 2026-07-01T07:05:16.445Z