Optimal Primal-Dual algorithms – APDO
We are interested in the minimization of a convex function under affine constraints. The goal of the project is to develop optimal primal-dual algorithms under the assumption of metric sub-regularity for the generalized gradient of the Lagrangian function. With an analogy to the unconstrained case, we will hopefully win an order of magnitude in the speed of convergence.
Project coordination
Olivier Fercoq (Laboratoire Traitement et Communication de l'Information)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
LTCI Laboratoire Traitement et Communication de l'Information
Help of the ANR 153,006 euros
Beginning and duration of the scientific project:
February 2021
- 42 Months
