Minisymposia

Title: Parameter choice for Tikhonov regularization
Organizer(s): Bangti Jin, Institute of Applied Math and Computational Science and Texas A&M University
Speakers: Stefan Kindermann, RICAM, Johannes Kepler University of Linz
Convergence of heuristic parameter choice rules

Tomoya Takeuchi, North Carolina State University
A regularization parameter for nonsmooth regularization

Ewout van den Berg, Stanford University
A root-finding approach for sparse recovery

Uno Hämarik, Institute of Applied Mathematics, Tartu University
On parameter choice in Tikhonov regularization in case of different information about noise level

Antoine Laurain, Humboldt University of Berlin
Multiphase image segmentation based on shape and topological sensitivity

Rosemery Renaut, Arizona State University
Parameter choice for TV regulation via Tikhonov methods

Christian Clason, Institute of Mathematics and Scientific Computing and University of Graz
Parameter choice for nonsmooth problems

Shuai Lu, Fudan University
Numerical differentiation by a Tikhonov regulation method based on the discrete cosine transform

Michael Hintermüller, Humboldt University of Berlin (Cancelled)
Abstract: Tikhonov regularization represents one of the most important techniques for solving inverse problems. However, its successful application relies heavily on the choice of one or several scalar parameters, a.k.a. regularization parameter, in the formulation, and the choice is often nontrivial. Recently, there have been important breakthroughs in developing rules for emerging formulations as well as in shedding new insights into known rules. This mini-symposium aims at bringing active researchers to discuss the status of the art. The proposed mini-symposium consists of two sessions, each with four speakers.

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