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math.NA2025
Low-rank approximation of analytic kernels
Marcus Webb
Many algorithms in scientific computing and data science take advantage of low-rank approximation of matrices and kernels, and understanding why nearly-low-rank structure occurs is…
math.NA2025★ 1 cited
A Riemannian Gradient Descent Method for the Least Squares Inverse Eigenvalue Problem
Alban Bloor Riley, Marcus Webb, Michael L. Baker
We address an algorithm for the least squares fitting of a subset of the eigenvalues of an unknown Hermitian matrix lying an an affine subspace, called the Lift and Projection (LP)…
math.NA2025
Computing accurate eigenvalues using a mixed-precision Jacobi algorithm
Nicholas J. Higham, Françoise Tisseur, Marcus Webb +1
We provide a rounding error analysis of a mixed-precision preconditioned Jacobi algorithm, which uses low precision to compute the preconditioner, applies it at high precision (amo…