A Taxonomy of Global Optimization Methods Based on Response Surfaces
Journal of Global Optimization
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Entropy search for information-efficient global optimization
The Journal of Machine Learning Research
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Model Guided Sampling Optimization (MGSO) is a novel expensive black-box optimization method based on a combination of ideas from Estimation of Distribution Algorithms and global optimization methods using Gaussian Processes. The algorithm is described and its implementation tested on three benchmark functions as a proof of concept.