285 citations · 499 across the 55 of their papers we have counts for
5 papers · 1 filter
Escaping local minima with derivative-free methods: a numerical investigation
Coralia Cartis, Lindon Roberts, Oliver Sheridan-Methven
We apply a state-of-the-art, local derivative-free solver, Py-BOBYQA, to global optimization problems, and propose an algorithmic improvement that is beneficial in this context. Ou…
Universal regularization methods - varying the power, the smoothness and the accuracy
Coralia Cartis, Nicholas I. M. Gould, Philippe L. Toint
Adaptive cubic regularization methods have emerged as a credible alternative to linesearch and trust-region for smooth nonconvex optimization, with optimal complexity amongst secon…
Sharp worst-case evaluation complexity bounds for arbitrary-order nonconvex optimization with inexpensive constraints
Coralia Cartis, Nick I. M. Gould, Philippe L. Toint
We provide sharp worst-case evaluation complexity bounds for nonconvex minimization problems with general inexpensive constraints, i.e.\ problems where the cost of evaluating/enfor…
Adaptive regularization with cubics on manifolds
Naman Agarwal, Nicolas Boumal, Brian Bullins +1
Adaptive regularization with cubics (ARC) is an algorithm for unconstrained, non-convex optimization. Akin to the popular trust-region method, its iterations can be thought of as a…
Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers
Coralia Cartis, Jan Fiala, Benjamin Marteau +1
We present DFO-LS, a software package for derivative-free optimization (DFO) for nonlinear Least-Squares (LS) problems, with optional bound constraints. Inspired by the Gauss-Newto…