3 papers
math.OC2026
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization
Zhehao Li, Yanchen Wu, Jian Chen +1
Data-driven inverse optimization seeks to estimate unknown parameters in an optimization model from observations of optimization solutions. Many existing methods are ineffective in…
stat.ME2026
The Promises of Multiple Experiments: Identifying Joint Distribution of Potential Outcomes
Peng Wu, Xiaojie Mao
Typical causal effects are defined based on the marginal distribution of potential outcomes. However, many real-world applications require causal estimands involving the joint dist…
stat.ME2026
Evaluating Surrogates in Individualized Treatment Rules
Zeyu Xu, Xiaojie Mao, Hao Mei +1
In many decision-making problems, the primary outcome is expensive, time-consuming, or difficult to observe, so individualized treatment rules (ITRs) may be instead learned from su…