Sait Cakmak, Raul Astudillo, Peter Frazier, Enlu Zhou
TL;DR研究了基于贝叶斯优化算法的目标函数，其中目标函数采用 VaR 或 CVaR 风险度量，算法通过将目标函数建模为高斯过程来提高采样效率，并在投资组合优化和鲁棒系统设计等领域得到了有效应用。
Abstract
We consider bayesian optimization of objective functions of the form $\rho[
F(x, W) ]$, where $F$ is a black-box expensive-to-evaluate function and $\rho$
denotes either the VaR or CVaR risk measure, computed with respect to the
randomness induced by the environmental random variable $