AI RESEARCH
Prescribe-then-Select: Adaptive Policy Selection for Contextual Stochastic Optimization
arXiv CS.LG
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ArXi:2509.08194v2 Announce Type: replace We address the problem of policy selection in contextual stochastic optimization (CSO), where covariates are available as contextual information and decisions must satisfy hard feasibility constraints. In many CSO settings, multiple candidate policies--arising from different modeling paradigms--exhibit heterogeneous performance across the covariate space, with no single policy uniformly dominating.