1 citations · 1 across the 7 of their papers we have counts for
7 papers
Shape-Constrained Distributional Optimization via Importance-Weighted Sample Average Approximation
Henry Lam, Zhenyuan Liu, Dashi I. Singham
Shape-constrained optimization arises in a wide range of problems including distributionally robust optimization (DRO) that has surging popularity in recent years. In the DRO liter…
Quantifying Distributional Input Uncertainty via Inflated Kolmogorov-Smirnov Confidence Band
Motong Chen, Henry Lam, Zhenyuan Liu
In stochastic simulation, input uncertainty refers to the propagation of the statistical noise in calibrating input models to impact output accuracy, in addition to the Monte Carlo…
Propagation of Input Tail Uncertainty in Rare-Event Estimation: A Light versus Heavy Tail Dichotomy
Zhiyuan Huang, Henry Lam, Zhenyuan Liu
We consider the estimation of small probabilities or other risk quantities associated with rare but catastrophic events. In the model-based literature, much of the focus has been d…
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…
Bootstrap in High Dimension with Low Computation
Henry Lam, Zhenyuan Liu
The bootstrap is a popular data-driven method to quantify statistical uncertainty, but for modern high-dimensional problems, it could suffer from huge computational costs due to th…
Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling
Mansur Arief, Zhepeng Cen, Zhenyuan Liu +4
Evaluating the performance of autonomous vehicles (AV) and their complex subsystems to high precision under naturalistic circumstances remains a challenge, especially when failure…
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…