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Christine A. Shoemaker

pySOT and POAP: An event-driven asynchronous framework for surrogate optimization



David Eriksson , David Bindel , Christine A. Shoemaker

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Efficient Multi-Objective Optimization through Population-based Parallel Surrogate Search



Taimoor Akhtar , Christine A. Shoemaker

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* Submitted to IEEE Transactions on Evolutionary Computation. This work is supported by the National Research Foundation, Prime Minister's Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme and by the National Science Foundation (NSF) grant CISE 1116298 
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Sensitivity Analysis for Computationally Expensive Models using Optimization and Objective-oriented Surrogate Approximations



Yilun Wang , Christine A. Shoemaker

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A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysis



Yilun Wang , Christine A. Shoemaker

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