Approximating integral operators by a standard Galerkin discretisation typically leads to dense matrices. To avoid the quadratic complexity it takes to compute and store a dense matrix, several approaches have been introduced including $\mathcal{H}$-matrices. The kernel function is approximated by a separable function, this leads to a low rank matrix. Interpolation is a robust and popular scheme, but requires us to interpolate in each spatial dimension, which leads to a complexity of $m^d$ for $m$-th order. Instead of interpolation we propose using quadrature on the kernel function represented with Green's formula. Due to the fact that we are integrating only over the boundary, we save one spatial dimension compared to the interpolation met...
A general, {\em rectangular} kernel matrix may be defined as $K_{ij} = \kappa(x_i,y_j)$ where $\kapp...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
We study the frequent problem of approximating a target matrix with a matrix of lower rank. We provi...
Approximating integral operators by a standard Galerkin discretisation typically leads to dense matr...
A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for ...
169 pagesKernel functions are used in a variety of scientific settings to measure relationships or i...
In this thesis, we consider the numerical solution of a large eigenvalue problem in which the integr...
This article deals with the solution of integral equations using collocation methods with almost lin...
AbstractAn efficient algorithm for the direct solution of a linear system associated with the discre...
The design of sparse quadratures for the approximation of integral operators related to symmetric po...
In this paper, we investigate the complexity of the numerical construction of the Hankel structured ...
AbstractA new approximation tool such as sums of Kronecker products is recently found to provide a s...
H 2-matrices can be used to construct efficient approximations of discretized integral operators. Th...
© 2018 Society for Industrial and Applied Mathematics. The design of sparse quadratures for the appr...
Submitted for publication to SIAMMatrices coming from elliptic Partial Differential Equations (PDEs)...
A general, {\em rectangular} kernel matrix may be defined as $K_{ij} = \kappa(x_i,y_j)$ where $\kapp...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
We study the frequent problem of approximating a target matrix with a matrix of lower rank. We provi...
Approximating integral operators by a standard Galerkin discretisation typically leads to dense matr...
A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for ...
169 pagesKernel functions are used in a variety of scientific settings to measure relationships or i...
In this thesis, we consider the numerical solution of a large eigenvalue problem in which the integr...
This article deals with the solution of integral equations using collocation methods with almost lin...
AbstractAn efficient algorithm for the direct solution of a linear system associated with the discre...
The design of sparse quadratures for the approximation of integral operators related to symmetric po...
In this paper, we investigate the complexity of the numerical construction of the Hankel structured ...
AbstractA new approximation tool such as sums of Kronecker products is recently found to provide a s...
H 2-matrices can be used to construct efficient approximations of discretized integral operators. Th...
© 2018 Society for Industrial and Applied Mathematics. The design of sparse quadratures for the appr...
Submitted for publication to SIAMMatrices coming from elliptic Partial Differential Equations (PDEs)...
A general, {\em rectangular} kernel matrix may be defined as $K_{ij} = \kappa(x_i,y_j)$ where $\kapp...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
We study the frequent problem of approximating a target matrix with a matrix of lower rank. We provi...