Stochastic Trace and Diagonal Estimator for Tensors

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Verma, Bhisham Dev, Pratap, Rameshwar, Kang, Keegan
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866917042194481152
author Verma, Bhisham Dev
Pratap, Rameshwar
Kang, Keegan
author_facet Verma, Bhisham Dev
Pratap, Rameshwar
Kang, Keegan
contents We consider the problem of estimating the trace and diagonal entries of an N-order tensor (where $N \geq 2$) 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.
format Preprint
id arxiv_https___arxiv_org_abs_2510_22157
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stochastic Trace and Diagonal Estimator for Tensors
Verma, Bhisham Dev
Pratap, Rameshwar
Kang, Keegan
Numerical Analysis
Statistics Theory
We consider the problem of estimating the trace and diagonal entries of an N-order tensor (where $N \geq 2$) 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.
title Stochastic Trace and Diagonal Estimator for Tensors
topic Numerical Analysis
Statistics Theory
url https://arxiv.org/abs/2510.22157