Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versatile tool to develop fast algorithms for addressing large-scale problems. While existing software packages for such matrices often focus on linear systems, their scope of applications is in fact much wider and includes, for example, matrix functions and eigenvalue problems. In this work, we present a new MATLAB toolbox called hm-toolbox, which encompasses this versatility with a broad set of tools for HODLR and HSS matrices, unmatched by existing software. While mostly based on algorithms that can be found in the literature, our toolbox also contains a few new algorithms as well as novel auxiliary functions. Being entirely based on MATLAB, our...
The efficient and accurate QR decomposition for matrices with hierarchical low-rank structures, such...
The standard algorithms for dense matrices become expensive for large matrices, since the number of ...
International audienceMatrices possessing a low-rank property arise in numerous scientific applicati...
Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versat...
Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versat...
In this paper we review the technique of hierarchical matrices and put it into the context of black-...
U ovom radu bavili smo se aproksimacijama niskog ranga i najpoznatijim algoritmima za iste. Temelj z...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
Many matrices in scientific computing, statistical inference, and machine learning exhibit sparse an...
The hierarchical (H-) matrix format allows storing a variety of dense matrices from certain applicat...
This self-contained monograph presents matrix algorithms and their analysis. The new technique enabl...
Abstract. Randomized sampling has recently been proven a highly efficient technique for computing ap...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
This dissertation presents several fast and stable algorithms for both dense and sparse matrices bas...
The efficient and accurate QR decomposition for matrices with hierarchical low-rank structures, such...
The standard algorithms for dense matrices become expensive for large matrices, since the number of ...
International audienceMatrices possessing a low-rank property arise in numerous scientific applicati...
Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versat...
Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versat...
In this paper we review the technique of hierarchical matrices and put it into the context of black-...
U ovom radu bavili smo se aproksimacijama niskog ranga i najpoznatijim algoritmima za iste. Temelj z...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
Many matrices in scientific computing, statistical inference, and machine learning exhibit sparse an...
The hierarchical (H-) matrix format allows storing a variety of dense matrices from certain applicat...
This self-contained monograph presents matrix algorithms and their analysis. The new technique enabl...
Abstract. Randomized sampling has recently been proven a highly efficient technique for computing ap...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
The multiplication of matrices is an important arithmetic operation in computational mathematics. In...
This dissertation presents several fast and stable algorithms for both dense and sparse matrices bas...
The efficient and accurate QR decomposition for matrices with hierarchical low-rank structures, such...
The standard algorithms for dense matrices become expensive for large matrices, since the number of ...
International audienceMatrices possessing a low-rank property arise in numerous scientific applicati...