A Bayesian optimization method that builds Gaussian process surrogates in a PCA-derived eigenshape basis, focusing on output-relevant directions, improves low-budget shape optimization.
A warped kernel improving ro- bustness in Bayesian optimization via random embeddings
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Modeling and Optimization with Gaussian Processes in Reduced Eigenbases -- Extended Version
A Bayesian optimization method that builds Gaussian process surrogates in a PCA-derived eigenshape basis, focusing on output-relevant directions, improves low-budget shape optimization.