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most citedA Riemannian Gradient Descent Method for the Least Squares Inverse Eigenvalue Problem

1 citations · 1 across the 10 of their papers we have counts for

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math.NA2026

Sketching Outside the Hilbert Space for the Infinite-Dimensional Randomised SVD

Morgan Lynch-Davies, Marcus Webb

In randomised numerical linear algebra, common choices for distributions of sketch vectors are isotropic, so that . Unfortunately, the natur…

math.NA2026

Computing accurate singular vectors and eigenvectors using mixed-precision Jacobi algorithms

Zhengbo Zhou, Françoise Tisseur, Marcus Webb

Mixed-precision variants of the Jacobi algorithm for symmetric positive definite eigenproblems and the one-sided Jacobi algorithm for singular value decompositions have recently be…

math.NA2026

Stable Hermite transforms via the Golub-Welsch algorithm

Marcus Webb, Georg Maierhofer

We introduce an efficient stable algorithm for transforms associated with expansions in Hermite functions interpolated at Hermite polynomial roots. The Hermite transform matrix can…

math.NA2026

T-systems: a theory of orthonormal functions with a tridiagonal differentiation matrix

Arieh Iserles, Marcus Webb

The starting point of this paper is that a spectral method is essentially a combination of an orthonormal basis of the underlying Hilbert space with Galerkin conditions. The choice…

math.NA2026

Computing accurate singular values using a mixed-precision one-sided Jacobi algorithm

Zhengbo Zhou, Françoise Tisseur, Marcus Webb

We present a relative forward error analysis of a mixed-precision preconditioned one-sided Jacobi algorithm, analogous to a two-sided version introduced in [N. J. Higham, F. Tisseu…