3 papers
math.NA2025
Why the noise model matters: A performance gap in learned regularization
Sebastian Banert, Christoph Brauer, Dirk Lorenz +1
This article addresses the challenge of learning effective regularizers for linear inverse problems. We analyze and compare several types of learned variational regularization agai…
math.NA2023
Acceleration and restart for the randomized Bregman-Kaczmarz method
Lionel Tondji, Ion Necoara, Dirk A. Lorenz
Optimizing strongly convex functions subject to linear constraints is a fundamental problem with numerous applications. In this work, we propose a block (accelerated) randomized Br…
math.NA2023
Adaptive Bregman-Kaczmarz: An Approach to Solve Linear Inverse Problems with Independent Noise Exactly
Lionel Tondji, Idriss Tondji, Dirk A. Lorenz
We consider the block Bregman-Kaczmarz method for finite dimensional linear inverse problems. The block Bregman-Kaczmarz method uses blocks of the linear system and performs iterat…