208 citations · 1.7k across the 69 of their papers we have counts for
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Euclid in a Taxicab: Sparse Blind Deconvolution with Smoothed l1/l2 Regularization
Audrey Repetti, Mai Quyen Pham, Laurent Duval +2
The l1/l2 ratio regularization function has shown good performance for retrieving sparse signals in a number of recent works, in the context of blind deconvolution. Indeed, it bene…
A forward-backward view of some primal-dual optimization methods in image recovery
Patrick L. Combettes, Laurent Condat, Jean-Christophe Pesquet +1
A wide array of image recovery problems can be abstracted into the problem of minimizing a sum of composite convex functions in a Hilbert space. To solve such problems, primal-dual…
A constrained-based optimization approach for seismic data recovery problems
Mai Quyen Pham, Caroline Chaux, Laurent Duval +1
Random and structured noise both affect seismic data, hiding the reflections of interest (primaries) that carry meaningful geophysical interpretation. When the structured noise is…
A Class of Randomized Primal-Dual Algorithms for Distributed Optimization
Jean-Christophe Pesquet, Audrey Repetti
Based on a preconditioned version of the randomized block-coordinate forward-backward algorithm recently proposed in [Combettes,Pesquet,2014], several variants of block-coordinate…
Playing with Duality: An Overview of Recent Primal-Dual Approaches for Solving Large-Scale Optimization Problems
Nikos Komodakis, Jean-Christophe Pesquet
Optimization methods are at the core of many problems in signal/image processing, computer vision, and machine learning. For a long time, it has been recognized that looking at the…
A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal
Mai Quyen Pham, Laurent Duval, Caroline Chaux +1
Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured "noises". As their amplitude may be greater than signals of interest…