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Recovering best statistical guarantees via the empirical divergence-based distributionally robust optimization
Lam, Henry - In: Operations research 67 (2019) 4, pp. 1090-1105
Persistent link: https://www.econbiz.de/10012062921
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Maximum likelihood estimation by Monte Carlo simulation : toward data-driven stochastic modeling
Peng, Yijie; Fu, Michael; Heidergott, Bernd; Lam, Henry - In: Operations research 68 (2020) 6, pp. 1896-1912
Persistent link: https://www.econbiz.de/10012392175
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Optimization-based calibration of simulation input models
Goeva, Aleksandrina; Lam, Henry; Qian, Huajie; Zhang, Bo - In: Operations research 67 (2019) 5, pp. 1362-1382
Persistent link: https://www.econbiz.de/10012107785
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Robust analysis in stochastic simulation : computation and performance guarantees
Ghosh, Soumyadip; Lam, Henry - In: Operations research 67 (2019) 1, pp. 232-249
Persistent link: https://www.econbiz.de/10012000817
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Tail analysis without parametric models : a worst-case perspective
Lam, Henry; Mottet, Clementine - In: Operations research 65 (2017) 6, pp. 1696-1711
Persistent link: https://www.econbiz.de/10011777905
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Subsampling to enhance efficiency in input uncertainty quantification
Lam, Henry; Qian, Huajie - In: Operations research 70 (2022) 3, pp. 1891-1913
Persistent link: https://www.econbiz.de/10013366289
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Enhanced balancing of bias-variance tradeoff in stochastic estimation : a minimax perspective
Lam, Henry; Zhang, Xinyu; Zhang, Xuhui - In: Operations research 71 (2023) 6, pp. 2352-2373
Persistent link: https://www.econbiz.de/10014445044
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Efficient learning for clustering and optimizing context-dependent designs
Li, Haidong; Lam, Henry; Peng, Yijie - In: Operations research 72 (2024) 2, pp. 617-638
Persistent link: https://www.econbiz.de/10014520851
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Uncertainty quantification and exploration for reinforcement learning
Dong, Jing; Lam, Henry - In: Operations research 72 (2024) 4, pp. 1689-1709
Persistent link: https://www.econbiz.de/10015045690
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Convergence of the core in assignment markets
Kanoria, Yash; Saban, Daniela; Sethuraman, Jay - In: Operations research 66 (2018) 3, pp. 620-636
Persistent link: https://www.econbiz.de/10011884262