Active Learning of Piecewise Gaussian Process Surrogates

Active learning of Gaussian process (GP) surrogates has been useful for optimizing experimental designs for physical/computer simulation experiments, and for steering data acquisition schemes in machine learning. In this paper, we develop a method for active learning of piecewise, Jump GP surrogates...

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Bibliographische Detailangaben

Hauptverfasser:	Park, Chiwoo, Waelder, Robert, Kang, Bonggwon, Maruyama, Benji, Hong, Soondo, Gramacy, Robert
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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