Search Results - subject:"stochastic gradient estimation"

Variance reduction for generalized likelihood ratio method by conditional Monte Carlo and randomized Quasi-Monte Carlo methods

Peng, Yijie; Fu, Michael; Hu, Jiaqiao; L'Ecuyer, Pierre; … - In: Journal of management science and engineering 7 (2022) 4, pp. 550-577

The generalized likelihood ratio (GLR) method is a recently introduced gradient estimation method for handling discontinuities in a wide range of sample performances. We put the GLR methods from previous work into a single framework, simplify regularity conditions to justify the unbiasedness of...

Persistent link: https://www.econbiz.de/10014315671

Copula sensitivity analysis for portfolio credit derivatives

Lei, Lei; Peng, Yijie; Fu, Michael; Hu, Jian-Qiang - In: European journal of operational research : EJOR 308 (2023) 1, pp. 455-466

Persistent link: https://www.econbiz.de/10014283065

A new likelihood ratio method for training artificial neural networks

Peng, Yijie; Xiao, Li; Heidergott, Bernd; Hong, L. Jeff; … - In: INFORMS journal on computing : JOC ; charting new … 34 (2022) 1, pp. 638-655

Persistent link: https://www.econbiz.de/10013361323

Minimax efficient finite-difference stochastic gradient estimators using black-box function evaluations

Lam, Henry; Li, Haidong; Zhang, Xuhui - In: Operations research letters 49 (2021) 1, pp. 40-47

Persistent link: https://www.econbiz.de/10012485995

Regression models augmented with direct stochastic gradient estimators

Fu, Michael; Qu, Huashuai - In: INFORMS journal on computing : JOC 26 (2014) 3, pp. 484-499

Persistent link: https://www.econbiz.de/10010399808