Nuclear Norm and Spectral Norm of Tensor Product

Abstract


We show that the nuclear norm of the tensor product of two tensors is not greater than the product of the nuclear norms of these two tensors. As an application, we give lower bounds for the nuclear norm of an arbitrary tensor. We show that the spectral norm of the tensor product of two tensors is not greater than the product of the spectral norm of one tensor, and the nuclear norm of another tensor. By this result, we present an alternative formula for the spectral norm of a tensor, and give some lower bounds for the product of the nuclear norm and the spectral norm of an arbitrary tensor. The first result also shows that the nuclear norm of the square matrix is a matrix norm. We then extend the concept of matrix norm to tensor norm. A real function defined for all real tensors is called a tensor norm if it is a norm for any tensor space with fixed dimensions, and the norm of the tensor product of two tensors is always not greater than the product of the norms of these two tensors. We show that the $1$-norm, the Frobenius norm and the nuclear norm of tensors are tensor norms but the infinity norm and the spectral norm of tensors are not tensor norms.

Time


October 14th, 2019

10:00 ~ 11:30

Speaker


Liqun Qi, The Hong Kong Polytechnic University

Room


Room 308, School of Information Management & Engineering, Shanghai University of Finance & Economics