2 papers
stat.ML2025
The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub +3
Data-driven stochastic optimization is ubiquitous in machine learning and operational decision-making problems. Sample average approximation (SAA) and model-based approaches such a…
cs.LG2025
Dissecting the Impact of Model Misspecification in Data-driven Optimization
Adam N. Elmachtoub, Henry Lam, Haixiang Lan +1
Data-driven optimization aims to translate a machine learning model into decision-making by optimizing decisions on estimated costs. Such a pipeline can be conducted by fitting a d…