Inverse Problems and High-Dimensional Estimation

Pierre Alquier is an associate professor at Universite Paris 7 and a research fellow at CREST. He holds a PhD from Universite Paris 6. His research themes are high dimensional estimation and agregation of estimators in statistics. Eric Gautier is an associate professor at ENSAE ParisTech and a researcher at CREST. He holds a PhD from the University of Rennes 1. His research is both in probability and theoretical econometrics. Regarding the second theme, he is particularly interested in inverse problems and high dimensional estimation and their applications to economics. Gilles Stoltz is a research fellow at CNRS, Ecole normale superieure and an affiliated professor at HEC Paris. He holds a PhD and an habilitation from Universite Paris-Sud, Orsay. His research themes concern sequential prediction of arbitrary sequences and its application to the theory of repeated games.

• Part I Lecture Notes on Inverse Problems: Inverse Problems in Statistics (Laurent Cavalier).- Part II Invited Contribution on Inverse Problems: Non Parametric Models with Instrumental Variables (Jean-Pierre Florens).- Part III Lecture Notes on High-Dimensional Estimation: High Dimensional Sparse Econometric Models: An Introduction (Alexandre Belloni and Victor Chernozhukov).- Part IV Invited Contributions on High-Dimensional Estimation: Model selection in Gaussian regression for high-dimensional data (Felix Abramovich and Vadim Grinshtein).- Bayesian Perspectives on Sparse Empirical Bayes Analysis (SEBA) (Natalia Bochkina and Ya’acov Ritov).- Part V Invited and Contributed Talks Given During the Summer School: List of the Courses.- List of the Invited Talks.- List of the Contributed Talks and Posters.

From the reviews: "This volume contains contributions from a summer school on ill-posed inverse problems and high dimensional estimation, along with other contributions. ... This book looks at their relevance to economic and econometric problems. ... provides a useful overview of the challenges and approaches to tackling inverse problems - I would certainly recommend it to a researcher fresh to the area." (David J. Hand, International Statistical Review, Vol. 81 (1), 2013)