Samuel Vaiter

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.

samuel.vaiter@u-bourgogne.fr @vaiter @svaiter

News

Apr 16, 2017
Model Consistency of Partly Smooth Regularizers accepted in TIT

After two long years in review, our paper with J. Fadili and G. Peyré Model Consistency of Partly Smooth Regularizers has been accepted for publication in IEEE Transactions on Information Theory.

Mar 20, 2017
Accelerated alternating descent methods published in JMIV

Our paper with A. Chambolle and P. Tan, Accelerated Alternating Descent Methods for Dykstra-like problems has been accepted for publication in Journal of Mathematical Imaging and Vision. The online first version is available here.

Feb 14, 2017
New preprint on non-uniqueness for the analysis Lasso

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.

Dec 3, 2016
CLEAR accepted in SIAM IS

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.

Jul 22, 2016
New preprint on accelerated alternating descent methods

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.