2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Higher-Order Coverage Errors of Batching Methods via Edgeworth Expansions on -Statistics
Shengyi He, Henry Lam
While batching methods have been widely used in simulation and statistics, it is open regarding their higher-order coverage behaviors and whether one variant is better than the oth…
Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems
Mansur Arief, Yuanlu Bai, Wenhao Ding +4
Rare-event simulation techniques, such as importance sampling (IS), constitute powerful tools to speed up challenging estimation of rare catastrophic events. These techniques often…
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…
Adaptive Importance Sampling for Efficient Stochastic Root Finding and Quantile Estimation
Shengyi He, Guangxin Jiang, Henry Lam +1
In solving simulation-based stochastic root-finding or optimization problems that involve rare events, such as in extreme quantile estimation, running crude Monte Carlo can be proh…