AI RESEARCH
Contextual Scenario Generation for Two-Stage Stochastic Programming
arXiv CS.LG
•
ArXi:2502.05349v2 Announce Type: replace-cross Two-stage stochastic programs (2SPs) are widely used for decision-making under uncertainty, but their practical deployment is often limited by the large number of scenarios needed to approximate the conditional distribution of uncertain outcomes. We study contextual scenario generation: given contextual information, learn to produce a small, user-specified set of surrogate scenarios that, when used as input into the 2SP, lead to high-quality 2SP decisions.