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11/01/2021
The degree of ill-posedness of composite linear ill-posed problems with focus on the impact of the non-compact Hausdorff moment operator
We consider compact composite linear operators in Hilbert space, where t...
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05/21/2021
Designing truncated priors for direct and inverse Bayesian problems
The Bayesian approach to inverse problems with functional unknowns, has ...
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12/21/2020
Nonlinear Tikhonov regularization in Hilbert scales with oversmoothing penalty: inspecting balancing principles
The analysis of Tikhonov regularization for nonlinear ill-posed equation...
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02/24/2020
Inverse learning in Hilbert scales
We study the linear ill-posed inverse problem with noisy data in the sta...
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08/16/2019
Regularization of linear ill-posed problems involving multiplication operators
We study regularization of ill-posed equations involving multiplication ...
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05/26/2019
Lepskii Principle in Supervised Learning
In the setting of supervised learning using reproducing kernel methods, ...
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02/14/2019
Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems
We study a non-linear statistical inverse learning problem, where we obs...
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06/03/2018
Analysis of regularized Nyström subsampling for regression functions of low smoothness
This paper studies a Nyström type subsampling approach to large kernel l...
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01/29/2018