Minisymposia

Title: Recent advances in the regularization of inverse problems
Organizer(s): Dr. Marcus Haltmeier, University of Vienna, Wien, Austria
Dr. Akhtar A. Khan, Rochester Institute of Technology, New York
Speakers: Frank Schöpfer, Helmut Schmidt Universitat
Iterative regularization methods for parameter identification problems in Banach spaces

Christian Clason, University of Graz
L1 data fitting for parameter identification problems for PDEs

Antonio Leitao, Federal University of Santa Catarina
Level-set approaches of L2-type for recovering shape and contrast in ill-posed problems

Taufiquar Khan, Clemson University
Maximizing distinguishability and sparsity regularization for the inverse problem in diffuse optical tomography

Cara Brooks, Rose-Hulman Institute of Technology
A generalized approach to the method of local regularization

Stefan Anzengruber, Radon Institute for Computational and Applied Mathematics
Convergence rates for Morozov's discrepancy principle

Annamaria Barbagallo, Universita degli Studi di Catania
Competitive financial equilibrium problems with policy interventions: Variational formulation and inverse problems

Marcus Haltmeier, University of Vienna Nordbergstrasse
Convergence rates for sparse regularization
Abstract: The mini-symposium "Recent advances in the regularization of inverse problems" will be devoted to recent advances in the theory and numerical techniques of regularization in the context of inverse and ill-posed problems and their applications. The session will evolve around the following themes: Inverse and ill-posed problems, regularization methods including sparsity regularization, non-quadratic regularization, local regularization concepts and other variants, applications to imaging problems and signal processing, and other applications.

Please address administrative questions to aipc@math.tamu.edu. Scientific questions should be addressed to the chair of the Scientific Program Committee: rundell AT math.tamu.edu
 

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