Yijie Peng

Orcid: 0000-0003-2584-8131

According to our database¹, Yijie Peng authored at least 66 papers between 2013 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Forward Learning for Gradient-based Black-box Saliency Map Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training.

[BibT_eX]

[DOI]

CoRR, 2024

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode.

[BibT_eX]

[DOI]

CoRR, 2024

Sample-Efficient Clustering and Conquer Procedures for Parallel Large-Scale Ranking and Selection.

[BibT_eX]

[DOI]

Zishi Zhang

Yijie Peng

CoRR, 2024

AlphaRank: An Artificial Intelligence Approach for Ranking and Selection Problems.

[BibT_eX]

[DOI]

Ruihan Zhou

L. Jeff Hong

Yijie Peng

CoRR, 2024

2023

Efficient Sampling Policy for Selecting a Subset With the Best.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., August, 2023

Copula sensitivity analysis for portfolio credit derivatives.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., July, 2023

Training Neural Networks without Backpropagation: A Deeper Dive into the Likelihood Ratio Method.

[BibT_eX]

[DOI]

CoRR, 2023

Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms.

[BibT_eX]

[DOI]

Jinyang Jiang

Jiaqiao Hu

Yijie Peng

CoRR, 2023

A Novel Noise Injection-based Training Scheme for Better Model Robustness.

[BibT_eX]

[DOI]

CoRR, 2023

POMDP-Based Ranking and Selection.

[BibT_eX]

[DOI]

Ruihan Zhou

Yijie Peng

Proceedings of the Winter Simulation Conference, 2023

A Simulation Optimization Method for Scheduling Automated Guided Vehicles in a Stochastic Warehouse Management System.

[BibT_eX]

[DOI]

Gongbo Zhang

Xiaotian Liu

Yijie Peng

Proceedings of the Winter Simulation Conference, 2023

Top-Two Thompson Sampling for Selecting Context-Dependent Best Designs.

[BibT_eX]

[DOI]

Xinbo Shi

Yijie Peng

Gongbo Zhang

Proceedings of the Winter Simulation Conference, 2023

Efficient Bandwidth Selection for Kernel Density Estimation.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2023

2022

Dynamic Sampling Allocation Under Finite Simulation Budget for Feasibility Determination.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2022

A New Likelihood Ratio Method for Training Artificial Neural Networks.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2022

Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange.

[BibT_eX]

[DOI]

CoRR, 2022

An Efficient Dynamic Sampling Policy for Monte Carlo Tree Search.

[BibT_eX]

[DOI]

Gongbo Zhang

Yijie Peng

Yilong Xu

Proceedings of the Winter Simulation Conference, 2022

Thompson Sampling Meets Ranking and Selection.

[BibT_eX]

[DOI]

Yijie Peng

Gongbo Zhang

Proceedings of the Winter Simulation Conference, 2022

Estimating Confidence Regions for Distortion Risk Measures and Their Gradients.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2022

Quantile-Based Policy Optimization for Reinforcement Learning.

[BibT_eX]

[DOI]

Jinyang Jiang

Yijie Peng

Jiaqiao Hu

Proceedings of the Winter Simulation Conference, 2022

Noise Optimization in Artificial Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

2021

Efficient Learning for Selecting Important Nodes in Random Network.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2021

Efficient Sampling Allocation Procedures for Optimal Quantile Selection.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2021

Computing Sensitivities for Distortion Risk Measures.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2021

Pathological Image Segmentation with Noisy Labels.

[BibT_eX]

[DOI]

CoRR, 2021

Noise Optimization for Artificial Neural Networks.

[BibT_eX]

[DOI]

Li Xiao

Zeliang Zhang

Yijie Peng

CoRR, 2021

Dynamic Sampling Policy For Subset Selection.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2021

Variance Reduction for Generalized Likelihood Ratio Method in Quantile Sensitivity Estimation.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2021

Gradient-Based Simulation Optimization for Economic Design of Control Charts.

[BibT_eX]

[DOI]

Gongbo Zhang

Yijie Peng

Shuhuai Yang

Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020

Stochastic Control Framework for Determining Feasible Alternatives in Sampling Allocation.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2020

Maximum Likelihood Estimation by Monte Carlo Simulation: Toward Data-Driven Stochastic Modeling.

[BibT_eX]

[DOI]

Oper. Res., 2020

Technical Note - Central Limit Theorems for Estimated Functions at Estimated Points.

[BibT_eX]

[DOI]

Oper. Res., 2020

On the Variance of Single-Run Unbiased Stochastic Derivative Estimators.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2020

Optimal unbiased estimation for expected cumulative discounted cost.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., 2020

Sequential Sampling for a Ranking and Selection Problem with Exponential Sampling Distributions.

[BibT_eX]

[DOI]

Gongbo Zhang

Haidong Li

Yijie Peng

Proceedings of the Winter Simulation Conference, 2020

Asynchronous Value Iteration for Markov Decision Processes with Continuous State Spaces.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2020

Context-Dependent Ranking and Selection under a Bayesian Framework.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2020

Confidence Intervals and Regions for Quantiles using Conditional Monte Carlo and Generalized Likelihood Ratios.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulation Conference, 2020

Dynamic Sampling Allocation for Selecting a Good Enough Alternative.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: An Effective Way to Improve Robustness.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

2019

Efficient Simulation Sampling Allocation Using Multifidelity Models.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2019

A Coordinate Optimization Approach for Concurrent Design.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2019

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Adversarial Defensiveness.

[BibT_eX]

[DOI]

CoRR, 2019

Efficient Sampling for Selecting Important Nodes in Random Network.

[BibT_eX]

[DOI]

CoRR, 2019

Preface.

[BibT_eX]

[DOI]

Yijie Peng

Asia Pac. J. Oper. Res., 2019

From Data to Stochastic Modeling and Decision Making: What Can We Do Better?

[BibT_eX]

[DOI]

Asia Pac. J. Oper. Res., 2019

Estimating Quantile Sensitivity for Financial Models with Correlations and Jumps.

[BibT_eX]

[DOI]

Proceedings of the 2019 Winter Simulation Conference, 2019

Dynamic Sampling Procedure for Decomposable Random Networks.

[BibT_eX]

[DOI]

Proceedings of the 2019 Winter Simulation Conference, 2019

optimizing outpatient Department Staffing Level using Multi-Fidelity Models.

[BibT_eX]

[DOI]

Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018

Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2018

Ranking and Selection as Stochastic Control.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2018

A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters.

[BibT_eX]

[DOI]

Oper. Res., 2018

Applications of generalized likelihood ratio method to distribution sensitivities and steady-state simulation.

[BibT_eX]

[DOI]

Discret. Event Dyn. Syst., 2018

A Review of Static and Dynamic Optimization for Ranking and Selection.

[BibT_eX]

[DOI]

Proceedings of the 2018 Winter Simulation Conference, 2018

Dynamic Sampling for Feasibility Determination.

[BibT_eX]

[DOI]

Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

Efficient Sampling Procedure for Selecting the Largest Stationary Probability of a Markov Chain.

[BibT_eX]

[DOI]

Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

2017

Myopic Allocation Policy With Asymptotically Optimal Sampling Rate.

[BibT_eX]

[DOI]

Yijie Peng

Michael C. Fu

IEEE Trans. Autom. Control., 2017

On the asymptotic analysis of quantile sensitivity estimation by Monte Carlo simulation.

[BibT_eX]

[DOI]

Proceedings of the 2017 Winter Simulation Conference, 2017

An optimization approach for team coordination through information sharing.

[BibT_eX]

[DOI]

Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016

Dynamic Sampling Allocation and Design Selection.

[BibT_eX]

[DOI]

INFORMS J. Comput., 2016

On the regularity conditions and applications for generalized likelihood ratio method.

[BibT_eX]

[DOI]

Yijie Peng

Michael C. Fu

Jian-Qiang Hu

Proceedings of the Winter Simulation Conference, 2016

Estimating distribution sensitivity using generalized likelihood ratio method.

[BibT_eX]

[DOI]

Yijie Peng

Michael C. Fu

Jian-Qiang Hu

Proceedings of the 13th International Workshop on Discrete Event Systems, 2016

2015

Non-monotonicity of probability of correct selection.

[BibT_eX]

[DOI]

Proceedings of the 2015 Winter Simulation Conference, 2015

2013

Efficient Simulation Resource Sharing and Allocation for Selecting the Best.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2013

A dynamic framework for statistical selection problems.

[BibT_eX]

[DOI]

Proceedings of the Winter Simulations Conference: Simulation Making Decisions in a Complex World, 2013

Yijie Peng

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...