M28. Regularization Methods and Applications in Statistics and Econometrics

Ill-posed inverse problems arise in many applications of statistics and econometrics. Typical examples are the estimation of a density function (with the deconvolution problem) or of a regression function (with the nonparametric instrumental regression). One main difference with standard cases is that the operator characterizing the inverse problem is a statistical object that is often unknown and must be estimated.

The objective of this mini-symposium is to gather experts and young researches to discuss about recent advances in regularization methods and applications in statistical and econometrics issues.

Organizers:
Pierre Maréchal, University of Toulouse, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Anne Vanhems, Toulouse Business School, France, This email address is being protected from spambots. You need JavaScript enabled to view it.

Speakers (in alphabetical order):
Fredrik Hildrum, Norwegian University of Science and Technology, Norway, This email address is being protected from spambots. You need JavaScript enabled to view it.
Total variation-based Lavrentiev regularization in Volterra equations of the first kind

Clément Marteau, University of Lyon 1, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Sparse Regularization for Mixture Problems

PLENARY SPEAKERS

Prof. Dr. Liliana Borcea

University of Michigan, USA
http://www-personal.umich.edu/~borcea/

Inverse scattering in random media, Electro-magnetic inverse problems, Effective properties of composite materials, transport in high contrast, heterogeneous media

Prof. Dr. Bernd Hofmann

Chemnitz University of Technology, Germany
https://www.tu-chemnitz.de/mathematik/inverse_probleme/hofmann/?en=1

Regularization of inverse and ill-posed problems

Prof. Dr. John C Schotland

Yale University, USA
https://gauss.math.yale.edu/~js4228/

Inverse problems with applications to imaging, Scattering theory, Waves in random media, Nano-scale optics, Coherence theory and quantum optics

Prof. Dr. Erkki Somersalo

Case Western Reserve University, USA
https://mathstats.case.edu/faculty/erkki-somersalo/

Computational and statistical inverse problems, Probabilistic methods for uncertainty quantification, Modeling of complex systems, Biomedical applications

Prof. Dr. Gunther Uhlmann

University of Washington, USA
https://sites.math.washington.edu/~gunther/

Inverse problems and imaging, Partial differential equations, Microlocal analysis, Scattering theory

Prof. Dr. Jun Zou

The Chinese University of Hong Kong, Hong Kong SAR
https://www.math.cuhk.edu.hk/~zou/

Numerical solutions of electromagnetic Maxwell systems and interface problems, inverse and ill-posed problems, preconditioned and domain decomposition methods