126 citations · 162 across the 6 of their papers we have counts for
6 papers
Majorization-Minimization Networks for Inverse Problems: An Application to EEG Imaging
Le Minh Triet Tran, Sarah Reynaud, Ronan Fablet +3
Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based approaches such as deep unrolling and m…
A Second-Order Majorant Algorithm for Nonnegative Matrix Factorization
Mai-Quyen Pham, Jérémy Cohen, Thierry Chonavel
Nonnegative Matrix Factorization (NMF) is a fundamental tool in unsupervised learning, widely used for tasks such as dimensionality reduction, feature extraction, representation le…
A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping
Mai Quyen Pham, Benoit Oudompheng, Jérôme I. Mars +1
The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced wi…
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 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 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…