2021/01/24 by Subhasish Basak, Sébastien Petit, Julien Bect +2 · 1 voice · 1 citation
Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Gaussian Processes and Bayesian Inference #Simulation Techniques and Applications
paper · pdf · doi:10.1007/978-3-030-95470-3_9
This article investigates the origin of numerical issues in maximum likelihood parameter estimation for Gaussian process (GP) interpolation and investigates simple but effective strategies for improving commonly used open-source software implementations. This work targets a basic problem but a host of studies, particularly in the literature of Bayesian optimization, rely on off-the-shelf GP implementations. For the conclusions of these studies to be reliable and reproducible, robust GP implementations are critical.