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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Expected Improvements for the Asynchronous Parallel Global Optimization of Expensive Functions: Potentials and Challenges
verfasst von : Janis Janusevskis, Rodolphe Le Riche, David Ginsbourger, Ramunas Girdziusas
Erschienen in: Learning and Intelligent Optimization
Verlag: Springer Berlin Heidelberg
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Sequential sampling strategies based on Gaussian processes are now widely used for the optimization of problems involving costly simulations. But Gaussian processes can also generate parallel optimization strategies. We focus here on a new, parameter free, parallel expected improvement criterion for asynchronous optimization. An estimation of the criterion, which mixes Monte Carlo sampling and analytical bounds, is proposed. Logarithmic speed-ups are measured on 1 and 9 dimensional functions.