NeuroPareto uses a calibrated Bayesian classifier, deep GP surrogates, and an online-trained acquisition network to outperform baselines on Pareto proximity and hypervolume in costly many-objective search.
Evolutionary optimiza- tion methods for high-dimensional expensive problems: A survey.IEEE/CAA Journal of Automatica Sinica, 11 (5):1092–1105
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NeuroPareto: Calibrated Acquisition for Costly Many-Goal Search in Vast Parameter Spaces
NeuroPareto uses a calibrated Bayesian classifier, deep GP surrogates, and an online-trained acquisition network to outperform baselines on Pareto proximity and hypervolume in costly many-objective search.