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Yijie Peng
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2020 – today
- 2025
- [j28]Yijie Peng
, Michael C. Fu
Generalized likelihood ratio method for stochastic models with uniform random numbers as inputs. Eur. J. Oper. Res. 321(2): 493-502 (2025) - 2024
- [j27]Haidong Li, Henry Lam, Yijie Peng
Efficient Learning for Clustering and Optimizing Context-Dependent Designs. Oper. Res. 72(2): 617-638 (2024) - [j26]Jiaqiao Hu, Xiangyu Yang
A Q-learning algorithm for Markov decision processes with continuous state spaces. Syst. Control. Lett. 187: 105782 (2024) - [c32]Tao Ren
RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search. ICAIF 2024: 752-760 - [c31]Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng:
One Forward is Enough for Neural Network Training via Likelihood Ratio Method. ICLR 2024 - [i17]Ruihan Zhou, L. Jeff Hong, Yijie Peng:
AlphaRank: An Artificial Intelligence Approach for Ranking and Selection Problems. CoRR abs/2402.00907 (2024) - [i16]Zishi Zhang, Yijie Peng:
Sample-Efficient Clustering and Conquer Procedures for Parallel Large-Scale Ranking and Selection. CoRR abs/2402.02196 (2024) - [i15]Jinyang Jiang, Xiaotian Liu, Tao Ren, Qinghao Wang, Yi Zheng, Yufu Du, Yijie Peng, Cheng Zhang:
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode. CoRR abs/2403.00318 (2024) - [i14]Zeliang Zhang, Jinyang Jiang, Zhuo Liu, Susan Liang, Yijie Peng, Chenliang Xu:
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training. CoRR abs/2403.12320 (2024) - [i13]Tao Ren, Zishi Zhang, Jinyang Jiang, Guanghao Li, Zeliang Zhang, Mingqian Feng, Yijie Peng:
FLOPS: Forward Learning with OPtimal Sampling. CoRR abs/2410.05966 (2024) - [i12]Yi Zheng, Zehao Li, Peng Jiang, Yijie Peng:
Dual-Agent Deep Reinforcement Learning for Dynamic Pricing and Replenishment. CoRR abs/2410.21109 (2024) - 2023
- [j25]Lei Lei
Copula sensitivity analysis for portfolio credit derivatives. Eur. J. Oper. Res. 308(1): 455-466 (2023) - [j24]Gongbo Zhang, Yijie Peng, Jianghua Zhang, Enlu Zhou:
Asymptotically Optimal Sampling Policy for Selecting Top-m Alternatives. INFORMS J. Comput. 35(6): 1261-1285 (2023) - [j23]Gongbo Zhang
Efficient Sampling Policy for Selecting a Subset With the Best. IEEE Trans. Autom. Control. 68(8): 4904-4911 (2023) - [c30]Haidong Li, Long Wang, Yijie Peng, Di Wang:
Efficient Bandwidth Selection for Kernel Density Estimation. WSC 2023: 552-563 - [c29]Gongbo Zhang, Xiaotian Liu, Yijie Peng:
A Simulation Optimization Method for Scheduling Automated Guided Vehicles in a Stochastic Warehouse Management System. WSC 2023: 3238-3249 - [c28]Ruihan Zhou, Yijie Peng:
POMDP-Based Ranking and Selection. WSC 2023: 3388-3399 - [c27]Xinbo Shi, Yijie Peng, Gongbo Zhang:
Top-Two Thompson Sampling for Selecting Context-Dependent Best Designs. WSC 2023: 3400-3411 - [i11]Zeliang Zhang, Jinyang Jiang, Minjie Chen, Zhiyuan Wang, Yijie Peng, Zhaofei Yu:
A Novel Noise Injection-based Training Scheme for Better Model Robustness. CoRR abs/2302.10802 (2023) - [i10]Jinyang Jiang, Jiaqiao Hu, Yijie Peng:
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms. CoRR abs/2305.07248 (2023) - [i9]Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng:
Training Neural Networks without Backpropagation: A Deeper Dive into the Likelihood Ratio Method. CoRR abs/2305.08960 (2023) - 2022
- [j22]Zhongshun Shi
Dynamic Sampling Allocation Under Finite Simulation Budget for Feasibility Determination. INFORMS J. Comput. 34(1): 557-568 (2022) - [j21]Yijie Peng
A New Likelihood Ratio Method for Training Artificial Neural Networks. INFORMS J. Comput. 34(1): 638-655 (2022) - [j20]Jiaqiao Hu, Yijie Peng, Gongbo Zhang, Qi Zhang:
A Stochastic Approximation Method for Simulation-Based Quantile Optimization. INFORMS J. Comput. 34(6): 2889-2907 (2022) - [c26]Li Xiao, Zeliang Zhang
Noise Optimization in Artificial Neural Networks. CASE 2022: 1595-1600 - [c25]Lei Lei, Christos Alexopoulos, Yijie Peng, James R. Wilson:
Estimating Confidence Regions for Distortion Risk Measures and Their Gradients. WSC 2022: 13-24 - [c24]Jinyang Jiang, Yijie Peng, Jiaqiao Hu:
Quantile-Based Policy Optimization for Reinforcement Learning. WSC 2022: 2712-2723 - [c23]Gongbo Zhang, Yijie Peng, Yilong Xu:
An Efficient Dynamic Sampling Policy for Monte Carlo Tree Search. WSC 2022: 2760-2771 - [c22]Yijie Peng, Gongbo Zhang:
Thompson Sampling Meets Ranking and Selection. WSC 2022: 3075-3086 - [i8]Haidong Li, Anzhi Sheng, Yijie Peng, Long Wang:
Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange. CoRR abs/2201.11324 (2022) - [i7]Jinyang Jiang, Jiaqiao Hu, Yijie Peng:
Quantile-Based Policy Optimization for Reinforcement Learning. CoRR abs/2201.11463 (2022) - [i6]Gongbo Zhang, Yijie Peng, Yilong Xu:
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search. CoRR abs/2204.12043 (2022) - 2021
- [j19]Yijie Peng
Efficient Sampling Allocation Procedures for Optimal Quantile Selection. INFORMS J. Comput. 33(1): 230-245 (2021) - [j18]Peter W. Glynn, Yijie Peng
Computing Sensitivities for Distortion Risk Measures. INFORMS J. Comput. 33(4): 1520-1532 (2021) - [j17]Haidong Li
Efficient Learning for Selecting Important Nodes in Random Network. IEEE Trans. Autom. Control. 66(3): 1321-1328 (2021) - [c21]Gongbo Zhang, Yijie Peng, Shuhuai Yang:
Gradient-Based Simulation Optimization for Economic Design of Control Charts. CASE 2021: 1979-1984 - [c20]Yijie Peng, Michael C. Fu, Jiaqiao Hu, Pierre L'Ecuyer, Bruno Tuffin:
Variance Reduction for Generalized Likelihood Ratio Method in Quantile Sensitivity Estimation. WSC 2021: 1-12 - [c19]Gongbo Zhang, Yijie Peng, Jianghua Zhang, Enlu Zhou:
Dynamic Sampling Policy For Subset Selection. WSC 2021: 1-12 - [i5]Li Xiao, Zeliang Zhang, Yijie Peng:
Noise Optimization for Artificial Neural Networks. CoRR abs/2102.04450 (2021) - [i4]Li Xiao, Yinhao Li, Luxi Qv, Xinxia Tian, Yijie Peng, S. Kevin Zhou:
Pathological Image Segmentation with Noisy Labels. CoRR abs/2104.02602 (2021) - 2020
- [j16]Zhenyu Cui, Michael C. Fu, Yijie Peng, Lingjiong Zhu:
Optimal unbiased estimation for expected cumulative discounted cost. Eur. J. Oper. Res. 286(2): 604-618 (2020) - [j15]Zhenyu Cui, Michael C. Fu, Jian-Qiang Hu, Yanchu Liu, Yijie Peng, Lingjiong Zhu:
On the Variance of Single-Run Unbiased Stochastic Derivative Estimators. INFORMS J. Comput. 32(2): 390-407 (2020) - [j14]Peter W. Glynn, Lin Fan, Michael C. Fu, Jian-Qiang Hu, Yijie Peng
Technical Note - Central Limit Theorems for Estimated Functions at Estimated Points. Oper. Res. 68(5): 1557-1563 (2020) - [j13]Yijie Peng
Maximum Likelihood Estimation by Monte Carlo Simulation: Toward Data-Driven Stochastic Modeling. Oper. Res. 68(6): 1896-1912 (2020) - [j12]Yijie Peng
Stochastic Control Framework for Determining Feasible Alternatives in Sampling Allocation. IEEE Trans. Autom. Control. 65(6): 2647-2653 (2020) - [c18]Gongbo Zhang, Chun-Hung Chen, Qing-Shan Jia
Dynamic Sampling Allocation for Selecting a Good Enough Alternative. CASE 2020: 1319-1324 - [c17]Li Xiao, Yijie Peng, L. Jeff Hong, Zewu Ke, Shuhuai Yang:
Training Artificial Neural Networks by Generalized Likelihood Ratio Method: An Effective Way to Improve Robustness. CASE 2020: 1343-1348 - [c16]Haidong Li, Henry Lam, Zhe Liang, Yijie Peng:
Context-Dependent Ranking and Selection under a Bayesian Framework. WSC 2020: 2060-2070 - [c15]Lei Lei, Christos Alexopoulos, Yijie Peng, James R. Wilson:
Confidence Intervals and Regions for Quantiles using Conditional Monte Carlo and Generalized Likelihood Ratios. WSC 2020: 2071-2082 - [c14]Xiangyu Yang
Asynchronous Value Iteration for Markov Decision Processes with Continuous State Spaces. WSC 2020: 2856-2866 - [c13]Gongbo Zhang, Haidong Li, Yijie Peng:
Sequential Sampling for a Ranking and Selection Problem with Exponential Sampling Distributions. WSC 2020: 2984-2995
2010 – 2019
- 2019
- [j11]Yijie Peng:
Preface. Asia Pac. J. Oper. Res. 36(6): 1902002:1-1902002:2 (2019) - [j10]Joost Berkhout
From Data to Stochastic Modeling and Decision Making: What Can We Do Better? Asia Pac. J. Oper. Res. 36(6): 1940012:1-1940012:20 (2019) - [j9]Yijie Peng
A Coordinate Optimization Approach for Concurrent Design. IEEE Trans. Autom. Control. 64(7): 2913-2920 (2019) - [j8]Yijie Peng
Efficient Simulation Sampling Allocation Using Multifidelity Models. IEEE Trans. Autom. Control. 64(8): 3156-3169 (2019) - [c12]Bowen Pang, Xiaolei Xie, Bernd Heidergott
optimizing outpatient Department Staffing Level using Multi-Fidelity Models. CASE 2019: 715-720 - [c11]Yijie Peng, Michael C. Fu, Jian-Qiang Hu, Lei Lei:
Estimating Quantile Sensitivity for Financial Models with Correlations and Jumps. WSC 2019: 962-973 - [c10]Haidong Li, Yijie Peng, Xiaoyun Xu, Chun-Hung Chen, Bernd Heidergott
Dynamic Sampling Procedure for Decomposable Random Networks. WSC 2019: 3752-3763 - [i3]Haidong Li, Xiaoyun Xu, Yijie Peng, Chun-Hung Chen:
Efficient Sampling for Selecting Important Nodes in Random Network. CoRR abs/1901.03466 (2019) - [i2]Li Xiao, Yijie Peng, L. Jeff Hong, Zewu Ke:
Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Adversarial Defensiveness. CoRR abs/1902.00358 (2019) - 2018
- [j7]Lei Lei
Applications of generalized likelihood ratio method to distribution sensitivities and steady-state simulation. Discret. Event Dyn. Syst. 28(1): 109-125 (2018) - [j6]Yijie Peng
A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters. Oper. Res. 66(2): 487-499 (2018) - [j5]Yijie Peng
Ranking and Selection as Stochastic Control. IEEE Trans. Autom. Control. 63(8): 2359-2373 (2018) - [j4]Yijie Peng
Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario. IEEE Trans. Autom. Control. 63(9): 3091-3097 (2018) - [c9]Yijie Peng, Jie Song, Jie Xu, Edwin K. P. Chong:
Dynamic Sampling for Feasibility Determination. CASE 2018: 887-892 - [c8]Haidong Li, Xiaoyun Xu, Yijie Peng, Chun-Hung Chen:
Efficient Sampling Procedure for Selecting the Largest Stationary Probability of a Markov Chain. CASE 2018: 899-905 - [c7]Yijie Peng, Chun-Hung Chen, Edwin K. P. Chong, Michael C. Fu:
A Review of Static and Dynamic Optimization for Ranking and Selection. WSC 2018: 1909-1920 - 2017
- [j3]Yijie Peng, Michael C. Fu:
Myopic Allocation Policy With Asymptotically Optimal Sampling Rate. IEEE Trans. Autom. Control. 62(4): 2041-2047 (2017) - [c6]Yijie Peng, Edward Huang, Jie Xu, Chun-Hung Chen:
An optimization approach for team coordination through information sharing. CASE 2017: 282-287 - [c5]Yijie Peng, Michael C. Fu, Peter W. Glynn, Jianqiang Hu:
On the asymptotic analysis of quantile sensitivity estimation by Monte Carlo simulation. WSC 2017: 2336-2347 - [i1]Yijie Peng, Edwin K. P. Chong, Chun-Hung Chen, Michael C. Fu:
Ranking and Selection as Stochastic Control. CoRR abs/1710.02619 (2017) - 2016
- [j2]Yijie Peng, Chun-Hung Chen, Michael C. Fu, Jian-Qiang Hu:
Dynamic Sampling Allocation and Design Selection. INFORMS J. Comput. 28(2): 195-208 (2016) - [c4]Yijie Peng, Michael C. Fu, Jian-Qiang Hu:
Estimating distribution sensitivity using generalized likelihood ratio method. WODES 2016: 123-128 - [c3]Yijie Peng, Michael C. Fu, Jian-Qiang Hu:
On the regularity conditions and applications for generalized likelihood ratio method. WSC 2016: 919-930 - 2015
- [c2]Yijie Peng, Chun-Hung Chen, Michael C. Fu, Jian-Qiang Hu:
Non-monotonicity of probability of correct selection. WSC 2015: 3678-3689 - 2013
- [j1]Yijie Peng, Chun-Hung Chen, Michael C. Fu, Jian-Qiang Hu:
Efficient Simulation Resource Sharing and Allocation for Selecting the Best. IEEE Trans. Autom. Control. 58(4): 1017-1023 (2013) - [c1]Yijie Peng, Michael C. Fu, Chun-Hung Chen, Jian-Qiang Hu:
A dynamic framework for statistical selection problems. WSC 2013: 908-921
Coauthor Index
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