2 papers
math.OC2021
How many samples are needed to reliably approximate the best linear estimator for a linear inverse problem?
Gernot Holler
The linear minimum mean squared error (LMMSE) estimator is the best linear estimator for a Bayesian linear inverse problem with respect to the mean squared error. It arises as the…
math.OC2018
A Bilevel Approach for Parameter Learning in Inverse Problems
Gernot Holler, Karl Kunisch, Richard C. Barnard
A learning approach to selecting regularization parameters in multi-penalty Tikhonov regularization is investigated. It leads to a bilevel optimization problem, where the lower lev…