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Found 2 papers, 2 papers with code
Robust Multi-Objective Bayesian Optimization Under Input Noise
In many manufacturing processes, the design parameters are subject to random input noise, resulting in a product that is often less performant than expected.
Bayesian Optimization of Risk Measures
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 $W$.
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