J
Jean-Christophe Pesquet
Researcher at Université Paris-Saclay
Publications - 387
Citations - 14714
Jean-Christophe Pesquet is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Convex optimization & Wavelet. The author has an hindex of 50, co-authored 364 publications receiving 13264 citations. Previous affiliations of Jean-Christophe Pesquet include University of Marne-la-Vallée & CentraleSupélec.
Papers
More filters
Proceedings ArticleDOI
Optimization of a Geman-McClure like criterion for sparse signal deconvolution
TL;DR: A stochastic block-coordinate descent method is proposed for recovering a sparse unknown signal from a set of observations by minimizing a least-squares fit criterion penalized by a Geman-McClure like potential.
Journal ArticleDOI
A Bit Allocation Method for Sparse Source Coding
TL;DR: In this article, the authors developed an efficient bit allocation strategy for subband-based image coding systems based on a rate-distortion optimality criterion and formulated the problem as a convex optimization problem.
Proceedings ArticleDOI
Majorize-Minimize adapted metropolis-hastings algorithm. Application to multichannel image recovery
TL;DR: A novel method is proposed for tuning the related drift term of Langevin diffusion where the proposal accounts for a directional component and is preconditioned by an adaptive matrix based on a Majorize-Minimize strategy.
Proceedings ArticleDOI
A preconditioned Forward-Backward approach with application to large-scale nonconvex spectral unmixing problems
TL;DR: This work combines the Forward-Backward algorithm with an alternating minimization strategy to address a broad class of optimization problems involving large-size signals and an application example to a nonconvex spectral unmixing problem will be presented.
Proceedings ArticleDOI
2D Dual-Tree Complex Biorthogonal M-Band Wavelet Transform
TL;DR: This work proposes to further extend this framework on two fronts by considering biorthogonal and complex M-band dual-tree decompositions, andDenoising results are provided to demonstrate the validity of the proposed design rules.