Yijie Wang – Optimization Online

Distributionally Robust Optimization via Targeted Integral Probability Metrics for General Data Processes

Published: 2026/05/28, Updated: 2026/07/05

Optimization in Data Science, Robust Optimization, Stochastic Programming distributionally robust optimization, heavy-tailed distributions, incomplete data, integral probability metrics, markovian data, outlier-corrupted data, semi-infinite programming

Distributionally robust optimization (DRO) provides a principled framework for decision-making under distributional uncertainty. Classical data-driven DRO frameworks typically construct ambiguity sets from distributional information, such as moment constraints, divergence neighborhoods, or Wasserstein balls, specified before the downstream loss is considered. We propose a task-aware DRO framework based on targeted integral probability metrics. The ambiguity set … Read more

Data-Driven Contextual Optimization with Gaussian Mixtures: Flow-Based Generalization, Robust Models, and Multistage Extensions

Published: 2025/08/16, Updated: 2025/09/16

Robust Optimization, Stochastic Programming contextual stochastic optimization, data-driven dynamic programming, distributionally robust optimization, gaussian mixture models, multistage stochastic programming, normalizing flows

Contextual optimization enhances decision quality by leveraging side information to improve predictions of uncertain parameters. However, existing approaches face significant challenges when dealing with multimodal or mixtures of distributions. The inherent complexity of such structures often precludes an explicit functional relationship between the contextual information and the uncertain parameters, limiting the direct applicability of parametric … Read more