Publications

Google Scholar: Yue Wang's Google Scholar 

Preprints

• RLAF: Reinforcement Learning from Automaton Feedback

Mahyar Alinejad, Alvaro Velasquez, Yue Wang, George Atia

• Game-Theoretic Understandings of Multi-Agent Systems with Multiple Objectives

Yue Wang 

• Distributionally Robust Markov Games with Average Reward

Zachary Roch, Yue Wang 

• Online Robust Multi-Agent Reinforcement Learning under Model Uncertainties

Zain Ulabedeen Farhat, Debamita Ghosh, George K. Atia, Yue Wang

• A Finite-Sample Analysis of Distributionally Robust Average-Reward Reinforcement Learning

Z. Roch, C, Zhang, G. Atia, Y. Wang

• Robust Constrained Reinforcement Learning

Y. Wang, F. Miao, S. Zou

Conference

2026

• ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learning

Debamita Ghosh, George K. Atia, Yue Wang

AAAI 2026

• Stabilizing Policy Gradient Methods via Reward Profiling

Shihab Ahmed, El houcine Bergou, Aritra Dutta, Yue Wang

AAAI 2026  (Oral)

2025

• A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward

Z. Roch, G. Atia, Y. Wang

International Conference on Machine Learning (ICML). 2025

• Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning

C. Zhang, Z, Jia, G. Atia, S. He, Y. Wang

International Conference on Machine Learning (ICML). 2025

• Bidirectional End-to-End Framework for Transfer from Abstract Models in Non-Markovian Reinforcement Learning 

M. Alinejad, P. Nwaorgu, C. Enyioha, Y. Wang, A. Velasquez, G. Atia

International Conference on Neuro-symbolic Systems (NeuS). 2025

• Model-Free Offline Reinforcement Learning with Enhanced Robustness 

C. Zhang, Z. Farhat, G. Atia, Y. Wang

International Conference on Learning Representations (ICLR), 2025

• Hybrid Offline Passive Grammatical Inference and Online Planning for Non-Markovian Tasks

M. Alinejad, A. Velasquez, Y. Wang, G. Atia

International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025

2024 and before

• A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch

Y. Wang, Z. Sun, S. Zou

Conference on Neural Information Processing Systems (NeurIPS), 2024

• Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic With Compatible Function Approximation

Y. Wang, Y. Wang, Y. Zhou, S. Zou

International Conference on Machine Learning (ICML), Jul. 2024

• Model-Free Robust Reinforcement Learning with Sample Complexity Analysis

Y. Wang, S. Zou, Y. Wang

Conference on Uncertainty in Artificial Intelligence (UAI), Barcelona, Spain, Jul. 2024

• Model-Free Robust Average-Reward Reinforcement Learning

Y. Wang, A. Velasquez, G. Atia, A. Prater-Bennette, S. Zou

International Conference on Machine Learning (ICML), Hawaii, USA, Jul. 2023

• A Robust and Constrained Multi-Agent Reinforcement Learning Method for Electric Vehicle AMoD Systems

S. He, Y. Wang, S. Han, S. Zou, F. Miao

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023  (Short version in AI4ABM Workshop at ICLR 2023)

• Robust Average-Reward Markov Decision Processes

Y. Wang, A. Velasquez, G. Atia, A. Prater-Bennette, S. Zou

Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, Feb. 2023  (Distinguished Award)

• Data-Driven Robust Multi-Agent Reinforcement Learning
  Y. Wang, Y. Wang, Y. Zhou, A. Velasquez, S. Zou
  IEEE International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2022

• Policy Gradient Method for Robust Reinforcement Learning
  Y. Wang, S. Zou
  International Conference on Machine Learning (ICML), Baltimore, USA, Jul. 2022

• Online Robust Reinforcement Learning with Model Uncertainty
  Y. Wang, S. Zou
  Conference on Neural Information Processing Systems (NeurIPS), Virtual, Dec. 2021

• Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation
  Y. Wang, Y. Zhou, S. Zou
  Conference on Neural Information Processing Systems (NeurIPS), Virtual, Dec. 2021 

• Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise
  Y. Wang, S. Zou
  Conference on Uncertainty in Artificial Intelligence (UAI), Aug. 2020  

Journal

• Achieving the Asymptotically Minimax Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach

Y. Wang, J. Xiong, S. Zou

Transactions on Machine Learning Research, 2024.

• Provably Efficient Offline Reinforcement Learning with Trajectory-Wise Reward
  T. Xu, Y. Wang, S. Zou, Y. Liang
  IEEE Transactions on Information Theory, 2024.

• Finite-Time Error Bounds for Greedy-GQ

Y. Wang, Y. Zhou, S. Zou

Machine Learning, Springer, 2024.

• Robust Average-Reward Reinforcement Learning

Y. Wang, A. Velasquez, G. Atia, A. Prater-Bennette, S. Zou

Journal of Artificial Intelligence Research, 2024.