activity
20102023
most citedA literature survey of low-rank tensor approximation techniques

54 citations · 208 across the 37 of their papers we have counts for

collaborators

46 papers

math.NA2023★ 2 cited

Analysis of eigenvalue condition numbers for a class of randomized numerical methods for singular matrix pencils

Daniel Kressner, Bor Plestenjak

The numerical solution of the generalized eigenvalue problem for a singular matrix pencil is challenging due to the discontinuity of its eigenvalues. Classically, such problems are…

math.NA2023

On the approximation of vector-valued functions by volume sampling

Daniel Kressner, Tingting Ni, André Uschmajew

Given a Hilbert space and a finite measure space , the approximation of a vector-valued function by a -dimensional subspace $\mathcal U \sub…

math.NA2023★ 8 cited

A mixed precision LOBPCG algorithm

Daniel Kressner, Yuxin Ma, Meiyue Shao

The locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm is a popular approach for computing a few smallest eigenvalues and the corresponding eigenvectors of…

math.NA2023★ 1 cited

Randomized low-rank approximation of parameter-dependent matrices

Daniel Kressner, Hei Yin Lam

This work considers the low-rank approximation of a matrix depending on a parameter in a compact set . Application areas that give rise to such p…

math.NA2022★ 1 cited

Speeding up Krylov subspace methods for computing f(A)b via randomization

Alice Cortinovis, Daniel Kressner, Yuji Nakatsukasa

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A…

math.NA2022

Hermite interpolation with retractions on manifolds

Axel Séguin, Daniel Kressner

Interpolation of data on non-Euclidean spaces is an active research area fostered by its numerous applications. This work considers the Hermite interpolation problem: finding a suf…