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.
Inverse distance weighting and radial basis function based surrogate model for high-dimensional expensive multi-objective optimization.Applied Soft Computing, 152:111194
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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.