Publication

Une version polyatomique de l'algorithme Frank-Wolfe pour résoudre le problème LASSO en grandes dimensions

Julien René Fageot, Matthieu Martin Jean-André Simeoni, Adrian Thibault Etienne Jarret
2022
Conference Papers

Abstract

Nous nous intéressons à la reconstruction parcimonieuse d’images à l’aide du problème d’optimisation régularisé LASSO. Dans de nombreuses applications pratiques, les grandes dimensions des objets à reconstruire limitent, voire empêchent, l’utilisation des méthodes de résolution proximales classiques. C’est le cas par exemple en radioastronomie. Nous détaillons dans cet article le fonctionnement de l’algorithme Frank-Wolfe Polyatomique, spécialement développé pour résoudre le problème LASSO dans ces contextes exigeants. Nous démontrons sa supériorité par rapport aux méthodes proximales dans des situations en grande dimension avec des mesures de Fourier, lors de la résolution de problèmes simulés inspirés de la radio-interférométrie.

Official source

https://infoscience.epfl.ch/entities/publication/4d1e27a6-03f2-4dca-bdb5-4cac6e3de9ba

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Julien René Fageot, Matthieu Martin Jean-André Simeoni, Adrian Thibault Etienne Jarret
2022
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4d1e27a6-03f2-4dca-bdb5-4cac6e3de9ba

About this result

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