In this article, I will first give a criterion for a generic m × n × n tensor to have rank n using simultaneously diagonalization of certain set of matrices. Then, in Section 3, I will study some properties (like irreducibility and diemnsion) of the varieties defined by the above si-multaneous diagonalization condition which are closely related to the commuting varieties. This criterion also provides a possible way to attack the ”Salmon Conjecture”. 1
It is shown that the maximal rank of m × n × ( m n - k ) tensors with k min {( m - 1 ) 2 /2 , ( ...
Given a d-dimensional tensor T:A ×…×A →F (where F is a field), the i-flattening rank of T is the ran...
AbstractThe typical rank (= maximal border rank) of tensors of a given size and the set of optimal b...
textabstractWe show that the border support rank of the tensor corresponding to two-by-two matrix m...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
AbstractThe concept of tensor rank was introduced in the 20s. In the 70s, when methods of Component ...
The Schmidt-Eckart-Young theorem for matrices states that the optimal rank-r approximation to a matr...
A tensor is a multi-dimensional data array, occurring ubiquitously in mathematics, physics, engineer...
This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of t...
This is a survey primarily about determining the border rank of tensors, especially those relevant f...
The singular value decomposition is among the most important algebraic tools for solving many approx...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
Comon’s conjecture on the equality of the rank and the symmetric rank of a symmetric tensor, a...
It is shown that the maximal rank of m × n × ( m n - k ) tensors with k min {( m - 1 ) 2 /2 , ( ...
Given a d-dimensional tensor T:A ×…×A →F (where F is a field), the i-flattening rank of T is the ran...
AbstractThe typical rank (= maximal border rank) of tensors of a given size and the set of optimal b...
textabstractWe show that the border support rank of the tensor corresponding to two-by-two matrix m...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
AbstractThe concept of tensor rank was introduced in the 20s. In the 70s, when methods of Component ...
The Schmidt-Eckart-Young theorem for matrices states that the optimal rank-r approximation to a matr...
A tensor is a multi-dimensional data array, occurring ubiquitously in mathematics, physics, engineer...
This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of t...
This is a survey primarily about determining the border rank of tensors, especially those relevant f...
The singular value decomposition is among the most important algebraic tools for solving many approx...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
Comon’s conjecture on the equality of the rank and the symmetric rank of a symmetric tensor, a...
It is shown that the maximal rank of m × n × ( m n - k ) tensors with k min {( m - 1 ) 2 /2 , ( ...
Given a d-dimensional tensor T:A ×…×A →F (where F is a field), the i-flattening rank of T is the ran...
AbstractThe typical rank (= maximal border rank) of tensors of a given size and the set of optimal b...