Uncertainty Quantification

''Over-Optimizing'' for Normality: Budget-Constrained Uncertainty Quantification for Contextual Decision-Making

We study uncertainty quantification for contextual stochastic optimization, focusing on weighted sample average approximation (wSAA), which uses machine-learned relevance weights based on covariates. Although wSAA is widely used for contextual …