GPareto: Gaussian Processes for Pareto Front Estimation and Optimization
Version 1.1.0

Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.

Package details

AuthorMickael Binois, Victor Picheny
Date of publication2017-06-29 05:30:09 UTC
MaintainerMickael Binois <[email protected]>
Package repositoryView on CRAN
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GPareto documentation built on July 4, 2017, 9:37 a.m.