This chapter looks at the structured matrix computations that arise in the context of various “svd-like” tensor decompositions.
People also ask
What is the difference between tensors and matrices?
What branch of math is tensors?
Why is a tensor not a matrix?
What is a tensor in simple terms?
May 3, 2021 · Our approach has three steps: map the structured matrix to tensors, use tensor compression algorithms, and map the compressed tensors back to ...
The contributions cover different aspects in the research field of structured matrices and tensors with applications. The first five papers [1–3, 5, 6] are ...
In mathematics, the structure tensor, also referred to as the second-moment matrix, is a matrix derived from the gradient of a function.
The paper is concerned with methods for computing the best low multilinear rank approximation of large and sparse tensors. Krylov-type methods have been used ...
Such techniques allow certain matrices to be represented in terms of simpler, structured matrices that have useful computational properties. Matrix ...
al. focusing on: CONFERENCES & conventions; MATRICES (Mathematics); TENSOR algebra; TOEPLITZ matrices; PUBLISHING; EXPONENTIAL functions; APPROXIMATION theory.
The use of tensor decompositions enables us to uncover latent structure in the problem and leads to compressed representations of the original matrix that can ...
Jun 12, 2013 · A matrix is just a grid of numbers, that's all. But a tensor has intrinsic structure beyond that grid. A tensor is actually just a vector in ...
Structured matrices and tensors. January 2012; Numerical Linear Algebra with Applications 19(1). 19(1). DOI:10.1002/nla.826. Authors: Ng Michael.