4 citations · 12 across the 4 of their papers we have counts for
7 papers
Constrained global optimization of functions with low effective dimensionality using multiple random embeddings
Coralia Cartis, Estelle Massart, Adilet Otemissov
We consider the bound-constrained global optimization of functions with low effective dimensionality, that are constant along an (unknown) linear subspace and only vary over the ef…
Scalable Derivative-Free Optimization for Nonlinear Least-Squares Problems
Coralia Cartis, Tyler Ferguson, Lindon Roberts
Derivative-free - or zeroth-order - optimization (DFO) has gained recent attention for its ability to solve problems in a variety of application areas, including machine learning,…
A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality
Coralia Cartis, Adilet Otemissov
We investigate the unconstrained global optimization of functions with low effective dimensionality, that are constant along certain (unknown) linear subspaces. Extending the techn…
Strong Evaluation Complexity Bounds for Arbitrary-Order Optimization of Nonconvex Nonsmooth Composite Functions
Coralia Cartis, Nick Gould, Philippe L. Toint
We introduce the concept of strong high-order approximate minimizers for nonconvex optimization problems. These apply in both standard smooth and composite non-smooth settings, and…
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…
A Derivative-Free Gauss-Newton Method
Coralia Cartis, Lindon Roberts
We present DFO-GN, a derivative-free version of the Gauss-Newton method for solving nonlinear least-squares problems. As is common in derivative-free optimization, DFO-GN uses inte…