Global Optimization of Gaussian processes

Understand

Gaussian processes~(Kriging) are interpolating data-driven models that are frequently applied in various disciplines.

• Often, Gaussian processes are trained on datasets and are subsequently embedded as surrogate models in optimization problems.
• These optimization problems are nonconvex and global optimization is desired.
• However, previous literature observed computational burdens limiting deterministic global optimization to Gaussian processes trained on few data points.