Yijie Peng

Orcid: 0000-0003-2584-8131

According to our database1, Yijie Peng authored at least 72 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Q-learning algorithm for Markov decision processes with continuous state spaces.
Syst. Control. Lett., 2024

Efficient Learning for Clustering and Optimizing Context-Dependent Designs.
Oper. Res., 2024

FLOPS: Forward Learning with OPtimal Sampling.
CoRR, 2024

Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training.
CoRR, 2024

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode.
CoRR, 2024

Sample-Efficient Clustering and Conquer Procedures for Parallel Large-Scale Ranking and Selection.
CoRR, 2024

AlphaRank: An Artificial Intelligence Approach for Ranking and Selection Problems.
CoRR, 2024

One Forward is Enough for Neural Network Training via Likelihood Ratio Method.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search.
Proceedings of the 5th ACM International Conference on AI in Finance, 2024

2023
Efficient Sampling Policy for Selecting a Subset With the Best.
IEEE Trans. Autom. Control., August, 2023

Copula sensitivity analysis for portfolio credit derivatives.
Eur. J. Oper. Res., July, 2023

Asymptotically Optimal Sampling Policy for Selecting Top-<i>m</i> Alternatives.
INFORMS J. Comput., 2023

Training Neural Networks without Backpropagation: A Deeper Dive into the Likelihood Ratio Method.
CoRR, 2023

Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms.
CoRR, 2023

A Novel Noise Injection-based Training Scheme for Better Model Robustness.
CoRR, 2023

POMDP-Based Ranking and Selection.
Proceedings of the Winter Simulation Conference, 2023

A Simulation Optimization Method for Scheduling Automated Guided Vehicles in a Stochastic Warehouse Management System.
Proceedings of the Winter Simulation Conference, 2023

Top-Two Thompson Sampling for Selecting Context-Dependent Best Designs.
Proceedings of the Winter Simulation Conference, 2023

Efficient Bandwidth Selection for Kernel Density Estimation.
Proceedings of the Winter Simulation Conference, 2023

2022
Dynamic Sampling Allocation Under Finite Simulation Budget for Feasibility Determination.
INFORMS J. Comput., 2022

A New Likelihood Ratio Method for Training Artificial Neural Networks.
INFORMS J. Comput., 2022

A Stochastic Approximation Method for Simulation-Based Quantile Optimization.
INFORMS J. Comput., 2022

Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange.
CoRR, 2022

An Efficient Dynamic Sampling Policy for Monte Carlo Tree Search.
Proceedings of the Winter Simulation Conference, 2022

Thompson Sampling Meets Ranking and Selection.
Proceedings of the Winter Simulation Conference, 2022

Estimating Confidence Regions for Distortion Risk Measures and Their Gradients.
Proceedings of the Winter Simulation Conference, 2022

Quantile-Based Policy Optimization for Reinforcement Learning.
Proceedings of the Winter Simulation Conference, 2022

Noise Optimization in Artificial Neural Networks.
Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

2021
Efficient Learning for Selecting Important Nodes in Random Network.
IEEE Trans. Autom. Control., 2021

Efficient Sampling Allocation Procedures for Optimal Quantile Selection.
INFORMS J. Comput., 2021

Computing Sensitivities for Distortion Risk Measures.
INFORMS J. Comput., 2021

Pathological Image Segmentation with Noisy Labels.
CoRR, 2021

Noise Optimization for Artificial Neural Networks.
CoRR, 2021

Dynamic Sampling Policy For Subset Selection.
Proceedings of the Winter Simulation Conference, 2021

Variance Reduction for Generalized Likelihood Ratio Method in Quantile Sensitivity Estimation.
Proceedings of the Winter Simulation Conference, 2021

Gradient-Based Simulation Optimization for Economic Design of Control Charts.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020
Stochastic Control Framework for Determining Feasible Alternatives in Sampling Allocation.
IEEE Trans. Autom. Control., 2020

Maximum Likelihood Estimation by Monte Carlo Simulation: Toward Data-Driven Stochastic Modeling.
Oper. Res., 2020

Technical Note - Central Limit Theorems for Estimated Functions at Estimated Points.
Oper. Res., 2020

On the Variance of Single-Run Unbiased Stochastic Derivative Estimators.
INFORMS J. Comput., 2020

Optimal unbiased estimation for expected cumulative discounted cost.
Eur. J. Oper. Res., 2020

Sequential Sampling for a Ranking and Selection Problem with Exponential Sampling Distributions.
Proceedings of the Winter Simulation Conference, 2020

Asynchronous Value Iteration for Markov Decision Processes with Continuous State Spaces.
Proceedings of the Winter Simulation Conference, 2020

Context-Dependent Ranking and Selection under a Bayesian Framework.
Proceedings of the Winter Simulation Conference, 2020

Confidence Intervals and Regions for Quantiles using Conditional Monte Carlo and Generalized Likelihood Ratios.
Proceedings of the Winter Simulation Conference, 2020

Dynamic Sampling Allocation for Selecting a Good Enough Alternative.
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.
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

2019
Efficient Simulation Sampling Allocation Using Multifidelity Models.
IEEE Trans. Autom. Control., 2019

A Coordinate Optimization Approach for Concurrent Design.
IEEE Trans. Autom. Control., 2019

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Adversarial Defensiveness.
CoRR, 2019

Efficient Sampling for Selecting Important Nodes in Random Network.
CoRR, 2019

Preface.
Asia Pac. J. Oper. Res., 2019

From Data to Stochastic Modeling and Decision Making: What Can We Do Better?
Asia Pac. J. Oper. Res., 2019

Estimating Quantile Sensitivity for Financial Models with Correlations and Jumps.
Proceedings of the 2019 Winter Simulation Conference, 2019

Dynamic Sampling Procedure for Decomposable Random Networks.
Proceedings of the 2019 Winter Simulation Conference, 2019

optimizing outpatient Department Staffing Level using Multi-Fidelity Models.
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.
IEEE Trans. Autom. Control., 2018

Ranking and Selection as Stochastic Control.
IEEE Trans. Autom. Control., 2018

A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters.
Oper. Res., 2018

Applications of generalized likelihood ratio method to distribution sensitivities and steady-state simulation.
Discret. Event Dyn. Syst., 2018

A Review of Static and Dynamic Optimization for Ranking and Selection.
Proceedings of the 2018 Winter Simulation Conference, 2018

Dynamic Sampling for Feasibility Determination.
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.
Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

2017
Myopic Allocation Policy With Asymptotically Optimal Sampling Rate.
IEEE Trans. Autom. Control., 2017

On the asymptotic analysis of quantile sensitivity estimation by Monte Carlo simulation.
Proceedings of the 2017 Winter Simulation Conference, 2017

An optimization approach for team coordination through information sharing.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016
Dynamic Sampling Allocation and Design Selection.
INFORMS J. Comput., 2016

On the regularity conditions and applications for generalized likelihood ratio method.
Proceedings of the Winter Simulation Conference, 2016

Estimating distribution sensitivity using generalized likelihood ratio method.
Proceedings of the 13th International Workshop on Discrete Event Systems, 2016

2015
Non-monotonicity of probability of correct selection.
Proceedings of the 2015 Winter Simulation Conference, 2015

2013
Efficient Simulation Resource Sharing and Allocation for Selecting the Best.
IEEE Trans. Autom. Control., 2013

A dynamic framework for statistical selection problems.
Proceedings of the Winter Simulations Conference: Simulation Making Decisions in a Complex World, 2013


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