Add to ORKGThèse présentée a ̀ la faculte ́ des sciences et techniques de l’ingénieur pour l’obtention du grade de docteur ès sciences et acceptée sur proposition du jur
Dans cette thèse nous traitons deux sujets. Le premier sujet concerne l'apprentissage statistique en...
Presented on September 6, 2018 from 3:05 p.m.-3:55 p.m. at the School of Mathematics, Skiles Room 00...
In this paper, we aim at recovering an unknown signal x0 from noisy L1measurements y=Phi*x0+w, where...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
International audienceSparsity constraints are now very popular to regularize inverse problems. We r...
Presented on August 31, 2018 from 2:00 p.m.-3:00 p.m. at the Georgia Institute of Technology (Georgi...
International audienceRegularization and Bayesian inference based methods have been successfully app...
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/119115/1/insr12167.pd
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 200
textabstractDuring the last two decades, sparsity has emerged as a key concept to solve linear and n...
International audienceThe Bayesian approach is considered for inverse problems with a typical forwar...
Develops the statistical approach to inverse problems with an emphasis on modeling and computations....
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
Taking the Lasso method as its starting point, this book describes the main ingredients needed to st...
Dans cette thèse nous traitons deux sujets. Le premier sujet concerne l'apprentissage statistique en...
Presented on September 6, 2018 from 3:05 p.m.-3:55 p.m. at the School of Mathematics, Skiles Room 00...
In this paper, we aim at recovering an unknown signal x0 from noisy L1measurements y=Phi*x0+w, where...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
International audienceSparsity constraints are now very popular to regularize inverse problems. We r...
Presented on August 31, 2018 from 2:00 p.m.-3:00 p.m. at the Georgia Institute of Technology (Georgi...
International audienceRegularization and Bayesian inference based methods have been successfully app...
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/119115/1/insr12167.pd
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 200
textabstractDuring the last two decades, sparsity has emerged as a key concept to solve linear and n...
International audienceThe Bayesian approach is considered for inverse problems with a typical forwar...
Develops the statistical approach to inverse problems with an emphasis on modeling and computations....
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
Taking the Lasso method as its starting point, this book describes the main ingredients needed to st...
Dans cette thèse nous traitons deux sujets. Le premier sujet concerne l'apprentissage statistique en...
Presented on September 6, 2018 from 3:05 p.m.-3:55 p.m. at the School of Mathematics, Skiles Room 00...
In this paper, we aim at recovering an unknown signal x0 from noisy L1measurements y=Phi*x0+w, where...