Add to ORKGAbstract. In this paper we present an efficient algorithm for computing a sparse null space basis for a full row rank matrix. We first apply the ideas of the Markowitz’s pivot selection criterion to a rank reducing algorithm to propose an efficient algorithm for computing sparse null space bases of full row rank matrices. We then describe how we can use the Dulmage-Mendelsohn decomposition to make the resulting algorithm more efficient. 1
(eng) We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial m...
Abstract. We introduce the problem of rank matrix factorisation (RMF). That is, we consider the deco...
We reduce the problem of computing the rank and a null-space basis of a univariate polynomial matrix...
Abstract. This paper presents a new combinatorial approach towards constructing a sparse basis for t...
This paper presents a combinatorial study on the problem of constructing a sparse basis forthe null...
The Null Space Problem is that of finding a sparsest basis for the null space (null basis) of a $t ...
The sparse null space basis problem is the following: $A t \times n$ matrix $A (t less than n)$ is ...
This paper presents a combinatorial study on the problem ofconstructing a sparse basis forthe null-s...
We present algorithms for computing a sparse basis for the null space of a sparse underdetermined m...
AbstractIn this paper, we propose a new method to efficiently compute a representation of an orthogo...
AbstractThe most widely used stable methods for numerical determination of the rank of a matrix A ar...
Abstract. This paper presents a new combinatorial approach towards constructing a sparse, implicit b...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many ...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many ...
A method is proposed for estimating the numerical rank of a sparse matrix. The method uses orthogona...
(eng) We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial m...
Abstract. We introduce the problem of rank matrix factorisation (RMF). That is, we consider the deco...
We reduce the problem of computing the rank and a null-space basis of a univariate polynomial matrix...
Abstract. This paper presents a new combinatorial approach towards constructing a sparse basis for t...
This paper presents a combinatorial study on the problem of constructing a sparse basis forthe null...
The Null Space Problem is that of finding a sparsest basis for the null space (null basis) of a $t ...
The sparse null space basis problem is the following: $A t \times n$ matrix $A (t less than n)$ is ...
This paper presents a combinatorial study on the problem ofconstructing a sparse basis forthe null-s...
We present algorithms for computing a sparse basis for the null space of a sparse underdetermined m...
AbstractIn this paper, we propose a new method to efficiently compute a representation of an orthogo...
AbstractThe most widely used stable methods for numerical determination of the rank of a matrix A ar...
Abstract. This paper presents a new combinatorial approach towards constructing a sparse, implicit b...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many ...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many ...
A method is proposed for estimating the numerical rank of a sparse matrix. The method uses orthogona...
(eng) We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial m...
Abstract. We introduce the problem of rank matrix factorisation (RMF). That is, we consider the deco...
We reduce the problem of computing the rank and a null-space basis of a univariate polynomial matrix...