Usually one avoids numerical algorithms involving operations with large, fully populated
matrices. Instead one tries to reduce all algorithms to matrix-vector multiplications involving …

Matrices with low-rank off-diagonal blocks are a versatile tool to perform matrix compression
and to speed up various matrix operations, such as the solution of linear systems. Often, the …

We use a bisection method B. Parlett, The Symmetric Eigenvalue Problem, Prentice-Hall,
Englewood Cliffs, NJ, 1980, p. 51 to compute the eigenvalues of a symmetric H_ℓ-matrix M …

The computation of eigenvalues is one of the core topics of numerical mathematics. We will
discuss an eigenvalue algorithm for the computation of inner eigenvalues of a large …

We investigate the application of the LR Cholesky algorithm to symmetric hierarchical
matrices, symmetric simple structured hierarchical matrices and symmetric hierarchically …

We present a method of almost linear complexity to approximate some (inner) eigenvalues
of symmetric self‐adjoint integral or differential operators. Using ℋ‐arithmetic the …

Resumen (English summary below) Las H-Matrices nacen como una potente herramienta
numérica para abordar aplicaciones cuyos datos generan estructuras que se sitúan entre …

We consider the interpolation problem with the inverse multiquadric radial basis function.
The problem usually produces a large dense linear system that has to be solved by iterative …

Extracting information as much and precise as possible from nondestructive measurements
remains a challenge, especially when advanced test applications are emerging in …

The standard algorithms for dense matrices become expensive for large matrices, since the
number of floating point operations often grows like n 3. Therefore it is necessary to have …