M Imani, SF Ghoreishi - 2020 American control conference …, 2020 - ieeexplore.ieee.org
Design has become a salient part of most of the scientific and engineering tasks, embracing a wide range of domains including real experimental settings (eg, material discovery or drug …
A Tran, T Wildey, S McCann - … of Computing and …, 2020 - asmedigitalcollection.asme.org
Bayesian optimization (BO) is an efiective surrogate-based method that has been widely used to optimize simulation-based applications. While the traditional Bayesian optimization …
Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear state-space models that provide a rich framework for modeling many complex dynamical …
SF Ghoreishi, M Imani - 2020 American Control Conference …, 2020 - ieeexplore.ieee.org
Stabilization of complex cyber-physical systems is extremely important in keeping the critical infrastructure and the environment safe. This is, in particular, critical in coupled …
Y Wu, J Hu, Q Zhou, S Wang, P Jin - Aerospace Science and Technology, 2020 - Elsevier
Multi-fidelity (MF) metamodel has attracted significant attention recently in simulation-based design and optimization. It can achieve a desirable modeling accuracy with relatively lower …
D Khatamsaz, L Peddareddygari, S Friedman… - AIAA Scitech 2020 …, 2020 - arc.aiaa.org
Multi-objective optimization is often a difficult task owing to the need to balance competing objectives. A typical approach to handling this is to estimate a Pareto frontier in objective …
A promising alternative to the traditional objectives-and-constraints formulation for optimization that uses multiple dominance relations has recently been developed. Optimal …
Searching for the optimal values of hyperparameters of a Machine Learning algorithm can be an extremely computationally expensive and awfully energivorous process. This paper …
B Liu - 2020 IEEE International Conference on Big Data and …, 2020 - ieeexplore.ieee.org
Bayesian optimization (BO) is a powerful paradigm for derivative-free global optimization of a black-box objective function (BOF) that is expensive to evaluate. However, the overhead of …