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09/12/2023
From low-rank retractions to dynamical low-rank approximation and back
In algorithms for solving optimization problems constrained to a smooth ...
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09/05/2023
Subspace Acceleration for a Sequence of Linear Systems and Application to Plasma Simulation
We present an acceleration method for sequences of large-scale linear sy...
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05/22/2023
Analysis of a class of randomized numerical methods for singular matrix pencils
The numerical solution of the generalized eigenvalue problem for a singu...
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04/06/2023
On the approximation of vector-valued functions by samples
Given a Hilbert space ℋ and a finite measure space Ω, the approximation ...
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02/24/2023
Randomized low-rank approximation of parameter-dependent matrices
This work considers the low-rank approximation of a matrix A(t) dependin...
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02/24/2023
A mixed precision LOBPCG algorithm
The locally optimal block preconditioned conjugate gradient (LOBPCG) alg...
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12/24/2022
Speeding up Krylov subspace methods for computing f(A)b via randomization
This work is concerned with the computation of the action of a matrix fu...
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12/23/2022
Hermite interpolation with retractions on manifolds
Interpolation of data on non-Euclidean spaces is an active research area...
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12/14/2022
Randomized Joint Diagonalization of Symmetric Matrices
Given a family of nearly commuting symmetric matrices, we consider the t...
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11/22/2022
Randomized sketching of nonlinear eigenvalue problems
Rational approximation is a powerful tool to obtain accurate surrogates ...
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11/21/2022
Approximation in the extended functional tensor train format
This work proposes the extended functional tensor train (EFTT) format fo...
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09/22/2022
Randomized low-rank approximation of monotone matrix functions
This work is concerned with computing low-rank approximations of a matri...
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08/04/2022
Streaming Tensor Train Approximation
Tensor trains are a versatile tool to compress and work with high-dimens...
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04/15/2022
Singular quadratic eigenvalue problems: Linearization and weak condition numbers
The numerical solution of singular eigenvalue problems is complicated by...
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04/06/2022
Improved parallel-in-time integration via low-rank updates and interpolation
This work is concerned with linear matrix equations that arise from the ...
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03/21/2022
Iterative Refinement of Schur decompositions
The Schur decomposition of a square matrix A is an important intermediat...
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02/15/2022
Low-rank tensor approximations for solving multi-marginal optimal transport problems
By adding entropic regularization, multi-marginal optimal transport prob...
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11/08/2021
Fast global spectral methods for three-dimensional partial differential equations
Global spectral methods offer the potential to compute solutions of part...
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09/22/2021
Improved variants of the Hutch++ algorithm for trace estimation
This paper is concerned with two improved variants of the Hutch++ algori...
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07/09/2021
Divide and conquer methods for functions of matrices with banded or hierarchical low-rank structure
This work is concerned with approximating matrix functions for banded ma...
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04/23/2021
Hierarchical adaptive low-rank format with applications to discretized PDEs
A novel compressed matrix format is proposed that combines an adaptive h...
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01/30/2021
A Flexible Power Method for Solving Infinite Dimensional Tensor Eigenvalue Problems
We propose a flexible power method for computing the leftmost, i.e., alg...
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08/26/2020
Low-rank updates of matrix functions II: Rational Krylov methods
This work develops novel rational Krylov methods for updating a large-sc...
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07/31/2020
Functional Tucker approximation using Chebyshev interpolation
This work is concerned with approximating a trivariate function defined ...
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07/19/2020
A bivariate extension of the Crouzeix-Palencia result with an application to Fréchet derivatives of matrix functions
A result by Crouzeix and Palencia states that the spectral norm of a mat...
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05/20/2020
On randomized trace estimates for indefinite matrices with an application to determinants
Randomized trace estimation is a popular and well studied technique that...
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04/14/2020
Norm and trace estimation with random rank-one vectors
A few matrix-vector multiplications with random vectors are often suffic...
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02/05/2020
Limited-memory polynomial methods for large-scale matrix functions
Matrix functions are a central topic of linear algebra, and problems req...
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02/04/2020
Compress-and-restart block Krylov subspace methods for Sylvester matrix equations
Block Krylov subspace methods (KSMs) comprise building blocks in many st...
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01/24/2020
Certified and fast computations with shallow covariance kernels
Many techniques for data science and uncertainty quantification demand e...
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09/17/2019
hm-toolbox: Matlab software for HODLR and HSS matrices
Matrices with hierarchical low-rank structure, including HODLR and HSS m...
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08/16/2019
Low-rank approximation in the Frobenius norm by column and row subset selection
A CUR approximation of a matrix A is a particular type of low-rank appro...
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05/23/2019
Recursive blocked algorithms for linear systems with Kronecker product structure
Recursive blocked algorithms have proven to be highly efficient at the n...
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03/06/2019
Low-rank updates and divide-and-conquer methods for quadratic matrix equations
In this work, we consider two types of large-scale quadratic matrix equa...
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02/06/2019
On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices
The problem of finding a k × k submatrix of maximum volume of a matrix A...
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01/12/2018
A fast spectral divide-and-conquer method for banded matrices
Based on the spectral divide-and-conquer algorithm by Nakatsukasa and Hi...
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11/04/2016