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Title:

Multi-fidelity Constrained Optimization for Stochastic Black-Box Simulators

Document type:
Konferenzbeitrag
Author(s):
Kislaya Ravi; Atul Agrawal; Hans-Joachim Bungartz; Phaedon-Stelios Koutsourelakis
Abstract:
Constrained optimization of the parameters of a simulator plays a crucial role in a design process. These problems become challenging when the simulator is stochastic, computationally expensive, and the parameter space is high-dimensional. One can efficiently perform optimization only by utilizing the gradient with respect to the parameters, but these gradients are unavailable in many legacy, black-box codes. We introduce the algorithm Scout-Nd ( Stochastic Constrained Optimization for N dimensi...     »
Book / Congress title:
Machine Learning and the Physical Sciences Workshop at the 37th conference on Neural Information Processing Systems (NeurIPS) December 15, 2023
Date of congress:
December 15, 2023
Year:
2023
Quarter:
4. Quartal
Year / month:
2023-12
Month:
Dec
Reviewed:
ja
Language:
en
WWW:
https://ml4physicalsciences.github.io/2023/files/NeurIPS_ML4PS_2023_106.pdf
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