MS 3: New approaches to the regularization of ill-posed problems

Organizer

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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