Global optimization
Numerical analysis: mathematics of scientific computing (2nd ed)
Numerical analysis: mathematics of scientific computing (2nd ed)
Bayesian Algorithms for One-Dimensional GlobalOptimization
Journal of Global Optimization
Efficient Global Optimization of Expensive Black-Box Functions
Journal of Global Optimization
A Radial Basis Function Method for Global Optimization
Journal of Global Optimization
A Taxonomy of Global Optimization Methods Based on Response Surfaces
Journal of Global Optimization
Computer experiments and global optimization
Computer experiments and global optimization
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Convergence Rates of Efficient Global Optimization Algorithms
The Journal of Machine Learning Research
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We consider the 1D Expected Improvement optimization based on Gaussian processes having spectral densities converging to zero faster than exponentially. We give examples of problems where the optimization trajectory is not dense in the design space. In particular, we prove that for Gaussian kernels there exist smooth objective functions for which the optimization does not converge on the optimum.