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Adaptive Design of Experiments Based on Gaussian Processes

Part of the Lecture Notes in Computer Science book series (LNAI,volume 9047)

Abstract

We consider a problem of adaptive design of experiments for Gaussian process regression. We introduce a Bayesian framework, which provides theoretical justification for some well-know heuristic criteria from the literature and also gives an opportunity to derive some new criteria. We also perform testing of methods in question on a big set of multidimensional functions.

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Correspondence to Maxim Panov .

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Burnaev, E., Panov, M. (2015). Adaptive Design of Experiments Based on Gaussian Processes. In: Gammerman, A., Vovk, V., Papadopoulos, H. (eds) Statistical Learning and Data Sciences. SLDS 2015. Lecture Notes in Computer Science(), vol 9047. Springer, Cham. https://doi.org/10.1007/978-3-319-17091-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-17091-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17090-9

  • Online ISBN: 978-3-319-17091-6

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