Ranking and selection as stochastic control Y Peng, EKP Chong, CH Chen, MC Fu IEEE Transactions on Automatic Control 63 (8), 2359-2373, 2018 | 83 | 2018 |
A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters Y Peng, MC Fu, JQ Hu, B Heidergott Operations Research 66 (2), 487-499, 2018 | 69 | 2018 |
Dynamic sampling allocation and design selection Y Peng, CH Chen, MC Fu, JQ Hu INFORMS Journal on Computing 28 (2), 195-208, 2016 | 57 | 2016 |
Myopic allocation policy with asymptotically optimal sampling rate Y Peng, MC Fu IEEE Transactions on Automatic Control 62 (4), 2041-2047, 2016 | 42 | 2016 |
Efficient simulation resource sharing and allocation for selecting the best Y Peng, CH Chen, MC Fu, JQ Hu IEEE Transactions on Automatic Control 58 (4), 1017-1023, 2012 | 33 | 2012 |
Efficient simulation sampling allocation using multifidelity models Y Peng, J Xu, LH Lee, J Hu, CH Chen IEEE Transactions on Automatic Control 64 (8), 3156-3169, 2018 | 25 | 2018 |
Gradient-based myopic allocation policy: An efficient sampling procedure in a low-confidence scenario Y Peng, CH Chen, MC Fu, JQ Hu IEEE Transactions on Automatic Control 63 (9), 3091-3097, 2017 | 25 | 2017 |
Maximum likelihood estimation by Monte Carlo simulation: Toward data-driven stochastic modeling Y Peng, MC Fu, B Heidergott, H Lam Operations Research 68 (6), 1896-1912, 2020 | 23 | 2020 |
Institute of electrical and electronics engineers B Feng, G Pedrielli, Y Peng, S Shashaani, E Song, C Corlu, L Lee, ... Inc.: Piscataway, NJ, USA, 1-12, 1963 | 23 | 1963 |
Validation of digital twins: challenges and opportunities EY Hua, S Lazarova-Molnar, DP Francis 2022 Winter Simulation Conference (WSC), 2900-2911, 2022 | 22 | 2022 |
On the variance of single-run unbiased stochastic derivative estimators Z Cui, MC Fu, JQ Hu, Y Liu, Y Peng, L Zhu INFORMS Journal on Computing 32 (2), 390-407, 2020 | 19 | 2020 |
Non-monotonicity of probability of correct selection Y Peng, CH Chen, MC Fu, JQ Hu 2015 Winter Simulation Conference (WSC), 3678-3689, 2015 | 19 | 2015 |
On the asymptotic analysis of quantile sensitivity estimation by Monte Carlo simulation Y Peng, MC Fu, PW Glynn, J Hu 2017 Winter Simulation Conference (WSC), 2336-2347, 2017 | 18 | 2017 |
Context-dependent ranking and selection under a bayesian framework H Li, H Lam, Z Liang, Y Peng 2020 winter simulation conference (WSC), 2060-2070, 2020 | 17 | 2020 |
Online validation of simulation-based digital twins exploiting time series analysis G Lugaresi, S Gangemi, G Gazzoni, A Matta 2022 Winter Simulation Conference (WSC), 2912-2923, 2022 | 16 | 2022 |
A new likelihood ratio method for training artificial neural networks Y Peng, L Xiao, B Heidergott, LJ Hong, H Lam INFORMS Journal on Computing 34 (1), 638-655, 2022 | 16 | 2022 |
Dynamic sampling allocation under finite simulation budget for feasibility determination Z Shi, Y Peng, L Shi, CH Chen, MC Fu INFORMS Journal on Computing 34 (1), 557-568, 2022 | 16 | 2022 |
Applications of generalized likelihood ratio method to distribution sensitivities and steady-state simulation L Lei, Y Peng, MC Fu, JQ Hu Discrete Event Dynamic Systems 28, 109-125, 2018 | 16 | 2018 |
Noise optimization in artificial neural networks L Xiao, Z Zhang, K Huang, J Jiang, Y Peng IEEE Transactions on Automation Science and Engineering, 2024 | 14 | 2024 |
Computing sensitivities for distortion risk measures PW Glynn, Y Peng, MC Fu, JQ Hu INFORMS Journal on Computing 33 (4), 1520-1532, 2021 | 14 | 2021 |