Generalized T-product Tensor Bernstein Bounds
Abstract
Since Kilmer et al. introduced the new multiplication method between two third-order tensors around 2008 and third-order tensors with such multiplication structure are also called as T-product tensors, T-product tensors have been applied to many fields in science and engineering, such as low-rank tensor approximation, signal processing, image feature extraction, machine learning, computer vision, and the multi-view clustering problem, etc. However, there are very few works dedicated to exploring the behavior of random T-product tensors. This work considers the problem about the tail behavior of the unitarily invariant norm for the summation of random symmetric T-product tensors. Majorization and antisymmetric Kronecker product tools are main techniques utilized to establish inequalities for unitarily norms of multivariate T-product tensors. The Laplace transform method is integrated with these inequalities for unitarily norms of multivariate T-product tensors to provide us with Bernstein Bounds estimation of Ky Fan -norm for functions of the symmetric random T-product tensors summation.
Keywords
Cite
@article{arxiv.2109.10880,
title = {Generalized T-product Tensor Bernstein Bounds},
author = {Shih Yu Chang and Yimin Wei},
journal= {arXiv preprint arXiv:2109.10880},
year = {2021}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2105.06078, arXiv:2105.06471