MS 3: New approaches to the regularization of ill-posed problems
Organizer
- Sergei Pereverzyev (Linz)
Abstract
Regularization theory constitutes a lively part of Numerical Analysis. In the symposium we are going to highlight the progress made in such directions as regularization in non-Hilbert spaces, regularization by sparsity constraints, multiparameter regularization. We also expect to present new applications of advanced regularization techniques in natural and life sciences.
List of speakers
-
Massimo Fornasier (Technical University of Munich, Germany):
A learning method for optimal parameter choice in inverse problems -
Bernd Hofmann (Technical University of Chemnitz, Germany):
About a deficit in low order convergence rates on the example of autoconvolution -
Barbara Kaltenbacher (Alpen Adria University of Klagenfurt, Austria):
A second order iterative regularization method for nonlinear problems -
Valeriya Naumova (Simula Research Laboratory, Norway):
Multi-penalty regularization for high-dimensional learning
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