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Jeudi 20 Novembre
| Heure: |
10:30 - 12:00 |
| Lieu: |
Salle B107, bâtiment B, Université de Villetaneuse |
| Résumé: |
Frank-Wolfe methods for convex quadratic optimization |
| Description: |
Mathieu Besançon I will go over some recent results on Frank-Wolfe methods, presenting the core aspects of the algorithms and highlight properties of the algorithms that make them relevant for convex quadratic optimization, despite the first-order access to the objective. In particular, we will go over the active set identification property some Frank-Wolfe variants enjoy and a use of linear system or linear optimization solvers to accelerate convergence and reach finite-time guarantees.
I will then present one application to sparse flow decomposition for RNA-seq data analysis. |
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