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stat.ME2026
Studentized Cheap Bootstrap: Achieving Higher-Order Coverage Accuracy with Low Computation
Shengyi He, Henry Lam, Yunhao Yan
The bootstrap is a versatile method for quantifying statistical uncertainty. Among its variants, a popular approach, the studentized bootstrap, provably achieves higher-order cover…
stat.ME2021
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…
stat.ME2021★ 2 cited
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…