17 citations · 84 across the 29 of their papers we have counts for
5 papers · 1 filter
OPM, a collection of Optimization Problems in Matlab
Serge Gratton, Philippe L. Toint
OPM is a small collection of CUTEst unconstrained and bound-constrained nonlinear optimization problems, which can be used in Matlab for testing optimization algorithms directly (i…
An adaptive regularization algorithm for unconstrained optimization with inexact function and derivatives values
N. I. M. Gould, Ph. L. Toint
An adaptive regularization algorithm for unconstrained nonconvex optimization is proposed that is capable of handling inexact objective-function and derivative values, and also of…
Adaptive Regularization Minimization Algorithms with Non-Smooth Norms and Euclidean Curvature
Serge Gratton, Philippe L. Toint
A regularization algorithm (AR1pGN) for unconstrained nonlinear minimization is considered, which uses a model consisting of a Taylor expansion of arbitrary degree and regularizati…
The Impact of Noise on Evaluation Complexity: The Deterministic Trust-Region Case
Stefania Bellavia, Gianmarco Gurioli, Benedetta Morini +1
Intrinsic noise in objective function and derivatives evaluations may cause premature termination of optimization algorithms. Evaluation complexity bounds taking this situation int…
Quadratic and Cubic Regularisation Methods with Inexact function and Random Derivatives for Finite-Sum Minimisation
Stefania Bellavia, Gianmarco Gurioli, Benedetta Morini +1
This paper focuses on regularisation methods using models up to the third order to search for up to second-order critical points of a finite-sum minimisation problem. The variant p…