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Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling.

, , , , , , , , and . CoRR, (2021)

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Minimax Efficient Finite-Difference Gradient Estimators., and . WSC, page 392-403. IEEE, (2019)On The Impacts of Tail Model Uncertainty in Rare-Event Estimation., and . WSC, page 950-961. IEEE, (2019)Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling., , , , , , , , and . CoRR, (2021)Accelerated Evaluation of Automated Vehicles based on Importance Sampling Techniques., , , , , , and . CoRR, (2016)Constructing simulation output Intervals under input uncertainty via Data sectioning., and . WSC, page 1551-1562. IEEE, (2018)Importance Sampling for Rare-Event Gradient Estimation., , , , and . WSC, page 3063-3074. IEEE, (2022)Resampling Stochastic Gradient Descent Cheaply., and . WSC, page 3681-3692. IEEE, (2023)Statistical Uncertainty Quantification for Expensive Black-Box Models: Methodologies and Input Uncertainty Applications.. WSC, page 1501-1515. IEEE, (2023)Evaluation of automated vehicles in the frontal cut-in scenario - An enhanced approach using piecewise mixture models., , , , and . ICRA, page 197-202. IEEE, (2017)Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast, , , , , , , , , and 12 other author(s). Sci. Signal., (2010)