457 citations · 696 across the 72 of their papers we have counts for
14 papers · 1 filter
Smoothed -Divergence Distributionally Robust Optimization
Zhenyuan Liu, Bart P. G. Van Parys, Henry Lam
In data-driven optimization, sample average approximation (SAA) is known to suffer from the so-called optimizer's curse that causes an over-optimistic evaluation of the solution pe…
Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework
Garud Iyengar, Henry Lam, Tianyu Wang
Empirical risk minimization (ERM) and distributionally robust optimization (DRO) are popular approaches for solving stochastic optimization problems that appear in operations manag…
Orthounimodal Distributionally Robust Optimization: Representation, Computation and Multivariate Extreme Event Applications
Henry Lam, Zhenyuan Liu, Xinyu Zhang
This paper studies a basic notion of distributional shape known as orthounimodality (OU) and its use in shape-constrained distributionally robust optimization (DRO). As a key motiv…
Higher-Order Expansion and Bartlett Correctability of Distributionally Robust Optimization
Shengyi He, Henry Lam
Distributionally robust optimization (DRO) is a worst-case framework for stochastic optimization under uncertainty that has drawn fast-growing studies in recent years. When the und…
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization
Yibo Zeng, Henry Lam
Established approaches to obtain generalization bounds in data-driven optimization and machine learning mostly build on solutions from empirical risk minimization (ERM), which depe…
On the Impossibility of Statistically Improving Empirical Optimization: A Second-Order Stochastic Dominance Perspective
Henry Lam
When the underlying probability distribution in a stochastic optimization is observed only through data, various data-driven formulations have been studied to obtain approximate op…