most citedA Multi-Fidelity Active Learning Method for Global Design Optimization Problems with Noisy Evaluations

4 citations · 4 across the 1 of their papers we have counts for

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math.OC2022★ 4 cited

A Multi-Fidelity Active Learning Method for Global Design Optimization Problems with Noisy Evaluations

Riccardo Pellegrini, Jeroen Wackers, Riccardo Broglia +3

A multi-fidelity (MF) active learning method is presented for design optimization problems characterized by noisy evaluations of the performance metrics. Namely, a generalized MF s…