I am a CNRS research associate (CR2) in Applied Mathematics at IMB (Université de Bourgogne, France). My current research interests focus on variational regularization in signal and image processing, convex analysis, sparsity and risk estimation.
Our work with A. Barbara and A. Jourani on non-uniqueness for the analysis Lasso is available at the following link Maximal solutions of sparse analysis regularization.
Our paper on re-fitting has been accepted for publication in SIAM Journal on Imaging Science. The preprint is available at the following link CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration.
Together with A. Chambolle and P. Tan, we extended recent results by Antonin and T. Pock on the acceleration of alternating minimization techniques for quadratic plus nons-mooth objectives depending on two variables, with an emphasis on the strongly convex case. The paper is available at Accelerated Alternating Descent Methods for Dykstra-like problems.
Together with C. Deledalle, N. Papadakis and J. Salmon, we proposed a new framework to remove parts of the systematic errors affecting popular restoration algorithms. This work is available at the following link CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration.
Our paper The Degrees of Freedom of Partly Smooth Regularizers has been accepted for publication in Annals of the Institute of Statistical Mathematics (AISM).