Frequentist coverage and sup-norm convergence rate in Gaussian process regression

16 Aug 2017 Yun Yang Anirban Bhattacharya Debdeep Pati

Gaussian process (GP) regression is a powerful interpolation technique due to its flexibility in capturing non-linearity. In this paper, we provide a general framework for understanding the frequentist coverage of point-wise and simultaneous Bayesian credible sets in GP regression... (read more)

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METHOD TYPE
Gaussian Process
Non-Parametric Classification