3 papers
cs.LG2023
The limitation of neural nets for approximation and optimization
Tommaso Giovannelli, Oumaima Sohab, Luis Nunes Vicente
We are interested in assessing the use of neural networks as surrogate models to approximate and minimize objective functions in optimization problems. While neural networks are wi…
math.OC2023
Full-Low Evaluation Methods For Bound and Linearly Constrained Derivative-Free Optimization
Clément W. Royer, Oumaima Sohab, Luis Nunes Vicente
Derivative-free optimization (DFO) consists in finding the best value of an objective function without relying on derivatives. To tackle such problems, one may build approximate de…
math.OC2021
Full-low evaluation methods for derivative-free optimization
Albert S. Berahas, Oumaima Sohab, Luis Nunes Vicente
We propose a new class of rigorous methods for derivative-free optimization with the aim of delivering efficient and robust numerical performance for functions of all types, from s…