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20242026
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math.NA2026

A Twin gradient method for unconstrained optimization

Anna De Magistris, Michiel E. Hochstenbach, Gerardo Toraldo

The paper introduces a Twin‑Step gradient method that runs two parallel gradient sequences and chooses step sizes to minimize the distance between them, with a hybrid fallback to a…

math.NA2026

Transpose-free linear algebra

Diana Halikias, Michiel E. Hochstenbach, Alex Townsend

We study the limitations of matrix-free algorithms that access a matrix only through forward matrix-vector products (matvecs) , without access to the transpose $A…

math.NA2026

Deterministic and randomized Kaczmarz methods for with applications to color image restoration

Wenli Wang, Duo Liu, Gangrong Qu +1

We study Kaczmarz type methods to solve consistent linear matrix equations. We first present a block Kaczmarz (BK) method that employs a deterministic cyclic row selection strategy…

math.NA2026

On spectral properties and fast initial convergence of the Kaczmarz method

Per Christian Hansen, Michiel E. Hochstenbach

The Kaczmarz method is successfully used for solving discretizations of linear inverse problems, especially in computed tomography where it is known as ART. Practitioners often obs…

math.NA2025

Numerical methods for eigenvalues of singular polynomial eigenvalue problems

Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak

Recently, three numerical methods for the computation of eigenvalues of singular matrix pencils, based on a rank-completing perturbation, a rank-projection, or an augmentation were…

math.NA2024

A subspace method for large-scale trace ratio problems

G. Ferrandi, M. E. Hochstenbach, M. R. Oliveira

A subspace method is introduced to solve large-scale trace ratio problems. This approach is matrix-free, requiring only the action of the two matrices involved in the trace ratio.…