## Prof. Sorin-Mihai GRAD, PhD, (Department of Applied Mathematics, ENSTA Paris, Polytechnic Institute of Paris): Relaxed-inertial proximal point type algorithms for problems involving strongly quasiconvex functions

In the framework of the research seminar Analysis and Optimization, **Prof. Dr. Sorin-Mihai GRAD** (Department of Applied Mathematics, ENSTA Paris, Polytechnic Institute of Paris), will give a talk on Thursday, 06.04.2023, starting at 12:30 pm, entitled:

## Relaxed-inertial proximal point type algorithms for problems involving strongly quasiconvex functions

Abstract:

Introduced in the 1970’s by Martinet for minimizing convex functions and extended shortly afterwards by Rockafellar towards monotone inclusion problems, the proximal point algorithm turned out to be a viable computational method for solving various classes of optimization problems even beyond the convex framework.

In this talk we propose a relaxed-inertial proximal point type algorithm for solving optimization problems consisting in minimizing strongly quasiconvex functions whose variables lie in finitely dimensional linear subspaces. The method is then extended for equilibrium functions involving strongly quasiconvex functions. Computational results confirm the theoretical advances.

The talk contains joint work with Felipe Lara and Raúl Tintaya Marcavillaca (both from University of Tarapacá).

The presentation will take place online, on the platform ZOOM, the access data can be found below:

https://zoom.us/j/98704786553?pwd=RXBCYy9GRjBTK0RTM2QxbkV4NFVudz09

Meeting ID: 987 0478 6553

Passcode: optimizare