4 citations · 4 across the 5 of their papers we have counts for
10 papers · 1 filter
Iterative Refinement of Schur decompositions
Zvonimir Bujanović, Daniel Kressner, Christian Schröder
The Schur decomposition of a square matrix is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and…
Divide and conquer methods for functions of matrices with banded or hierarchical low-rank structure
Alice Cortinovis, Daniel Kressner, Stefano Massei
This work is concerned with approximating matrix functions for banded matrices, hierarchically semiseparable matrices, and related structures. We develop a new divide-and-conquer m…
Hierarchical adaptive low-rank format with applications to discretized PDEs
Stefano Massei, Leonardo Robol, Daniel Kressner
A novel compressed matrix format is proposed that combines an adaptive hierarchical partitioning of the matrix with low-rank approximation. One typical application is the approxima…
Low-rank updates of matrix functions II: Rational Krylov methods
Bernhard Beckermann, Alice Cortinovis, Daniel Kressner +1
This work develops novel rational Krylov methods for updating a large-scale matrix function f(A) when A is subject to low-rank modifications. It extends our previous work in this c…
Norm and trace estimation with random rank-one vectors
Zvonimir Bujanović, Daniel Kressner
A few matrix-vector multiplications with random vectors are often sufficient to obtain reasonably good estimates for the norm of a general matrix or the trace of a symmetric positi…
Compress-and-restart block Krylov subspace methods for Sylvester matrix equations
Daniel Kressner, Kathryn Lund, Stefano Massei +1
Block Krylov subspace methods (KSMs) comprise building blocks in many state-of-the-art solvers for large-scale matrix equations as they arise, e.g., from the discretization of part…