457 citations · 696 across the 72 of their papers we have counts for
7 papers · 1 filter
Context-dependent Ranking and Selection under a Bayesian Framework
Haidong Li, Henry Lam, Zhe Liang +1
We consider a context-dependent ranking and selection problem. The best design is not universal but depends on the contexts. Under a Bayesian framework, we develop a dynamic sampli…
Efficient Learning for Clustering and Optimizing Context-Dependent Designs
Haidong Li, Henry Lam, Yijie Peng
We consider a simulation optimization problem for a context-dependent decision-making. A Gaussian mixture model is proposed to capture the performance clustering phenomena of conte…
Rare-Event Simulation for Neural Network and Random Forest Predictors
Yuanlu Bai, Zhiyuan Huang, Henry Lam +1
We study rare-event simulation for a class of problems where the target hitting sets of interest are defined via modern machine learning tools such as neural networks and random fo…
Convolution Bounds on Quantile Aggregation
Jose Blanchet, Henry Lam, Yang Liu +1
Quantile aggregation with dependence uncertainty has a long history in probability theory with wide applications in finance, risk management, statistics, and operations research. U…
Minimax Efficient Finite-Difference Stochastic Gradient Estimators Using Black-Box Function Evaluations
Henry Lam, Haidong Li, Xuhui Zhang
Standard approaches to stochastic gradient estimation, with only noisy black-box function evaluations, use the finite-difference method or its variants. While natural, it is open t…
A Distributionally Robust Optimization Approach to the NASA Langley Uncertainty Quantification Challenge
Yuanlu Bai, Zhiyuan Huang, Henry Lam
We study a methodology to tackle the NASA Langley Uncertainty Quantification Challenge problem, based on an integration of robust optimization, more specifically a recent line of r…