Thursday, 13:45 - 14:10 h, Room: H 3003A


Stephen Billups
Managing the trust region and sample set for regression model based methods for optimizing noisy functions without derivatives


The presence of noise or uncertainty in function evaluations can negatively impact the performance of model based trust-region algorithms for derivative free optimization. One remedy for this problem is to use regression models, which are less sensitive to noise; and this approach can be enhanced by using weighted regression. But this raises questions of how to efficiently select sample points for model construction and how to manage the trust region radius, taking noise into account. This talk proposes strategies for addressing these questions and presents an algorithm based on these strategies.


Talk 2 of the invited session Thu.2.H 3003A
"Addressing noise in derivative-free optimization" [...]
Cluster 6
"Derivative-free & simulation-based optimization" [...]


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