arXiv Machine Learning June 4, 2026 By David Islip, Roy H. Kwon, Sanghyeon Bae, Woo Chang Kim

Contextual Scenario Generation for Two-Stage Stochastic Programming

Read the original on arXiv Machine Learning →

arXiv:2502. 05349v2 Announce Type: replace-cross Abstract: 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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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