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.

Invited Speakers:
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 regularisation of monotone problems

Mirza Karamehmedovic, Technical University of Denmark, Denmark, This email address is being protected from spambots. You need JavaScript enabled to view it.
Localization of moving sources: uniqueness, stability, and Bayesian inference

Pierre Maréchal, University of Toulouse, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
On the deconvolution of radom variables

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

Elena Resmerita, University of Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
On Hamilton-Jacobi PDEs and image denoising models with certain non-additive noise

Tuomo Valkonen, Escuela Politécnica Nacional, Ecuador; University of Helsinki, Finland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Regularisation, optimisation, subregularity

Anne Vanhems, Toulouse Business School, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
A mollifier approach to the nonparametric instrumental regression problem