Bernstein Concentration Inequalities for Tensors via Einstein Products

02/08/2019
by   Z. Luo, et al.
0

A generalization of the Bernstein matrix concentration inequality to random tensors of general order is proposed. This generalization is based on the use of Einstein products between tensors, from which a strong link can be established between matrices and tensors, in turn allowing exploitation of existing results for the former.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/20/2019

Sparse random tensors: concentration, regularization and applications

We prove a non-asymptotic concentration inequality of sparse inhomogeneo...
research
08/12/2020

A matrix concentration inequality for products

We present a non-asymptotic concentration inequality for the random matr...
research
06/07/2020

Tensors over Semirings for Latent-Variable Weighted Logic Programs

Semiring parsing is an elegant framework for describing parsers by using...
research
05/10/2023

On the tubular eigenvalues of third-order tensors

This paper introduces the notion of tubular eigenvalues of third-order t...
research
01/28/2020

A Partial Information Decomposition Based on Causal Tensors

We propose a partial information decomposition based on the newly introd...
research
01/07/2015

An Introduction to Matrix Concentration Inequalities

In recent years, random matrices have come to play a major role in compu...
research
07/22/2019

Reverse-order law for core inverse of tensors

The notion of the core inverse of tensors with the Einstein product was ...

Please sign up or login with your details

Forgot password? Click here to reset