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Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels
  • Quality

Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels

Publication:
Journal of Quality Technology
Date:
September 2021
Issue:
Volume 53 Issue 4
Pages:
pp. 410-420
Author(s):
Zhang, Qiong, Chien, Peter, Liu, Qing, Xu, Li, Hong, Yili

Abstract

Computer models with both quantitative and qualitative inputs frequently arise in science, engineering and business. Mixed-input Gaussian process models have been used for emulating such models. The key in building this emulator is to accurately estimate the covariance between different categorical levels of the qualitative inputs. This problem is challenging when the number of categorical levels is large. We propose a sparse covariance estimation approach to estimating the covariance matrix with a large number of categorical levels for the mixed-input Gaussian process emulator. The effectiveness of this approach is illustrated with an application of IO operation modes in high performance computing systems.

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