Publication and Preprint

Journal Paper

• Yuhao Wang, Enlu Zhou (2024), Online Bayesian Risk-Averse Reinforcement Learning, submitted.
• Yifan Lin, Yuhao Wang (co-first author), Enlu Zhou (2024), Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate, submitted.
• Yuhao Wang, Enlu Zhou (2024), Ranking and Selection with Streaming Input Data: Joint Optimization of Data Collection and Simulation, submitted.
• Alexander Shapiro, Enlu Zhou,  Yifan Lin, and Yuhao Wang (2023), Episodic Bayesian Optimal Control with Unknown Randomness Distributions, submitted.
• Yuhao Wang, Enlu Zhou (2024), Optimal Computing Budget Allocation for Data-driven Ranking and Selection, INFORMS Journal on Optimization.
• Sait Cakmak, Yuhao Wang, Siyang Gao, Enlu Zhou (2023), Contextual Ranking and Selection with Gaussian Processes and OCBA, ACM Transactions on Modeling and Computer Simulation.
• Di Wu, Yuhao Wang, Enlu Zhou (2022), Data-driven Ranking and Selection under Input Uncertainty, Operations Research.
• Yifan Lin, Yuhao Wang (co-first author), Enlu Zhou (2022), Risk-averse Contextual Multi-arm Bandit Problem with Linear Payoff, Journal of Systems Science and Systems Engineering.

Conference Paper

• Yuhao Wang, Seong-Hee Kim, Enlu Zhou (2023), Selection of the Best System with an Optimized Continuous Variable, accepted by 2024 Winter Simulation Conference.
• Yuhao Wang, Enlu Zhou (2023), Bayesian Risk-Averse Q-Learning with Streaming Observations, NeurIPS 2023.
  • Best Theoretical Paper Award – Runner-up (18th DMDA workshop, 2023)
  • INFORMS Poster Competition – Finalist (INFORMS 2023)
  • ICML workshop: PAC-Bayes Meets Interactive Learning (2023)
• Yuhao Wang, Enlu Zhou (2023), Input Data Collection versus Simulation: Simultaneous Resource Allocation, 2023 Winter Simulation Conference.
• Yuhao Wang, Enlu Zhou (2022), Fixed Budget Ranking and Selection with Streaming Input Data, 2022 Winter Simulation Conference.
  • Best Contributed Theoretical Paper – Winner.