Publication

A complete list of papers is on Google Scholar

See The Gambler's Problem and Beyond for my most representative work

Conference papers

1. Few-Shot Diffusion Models Escape the Curse of Dimensionality
   Ruofeng Yang, Bo Jiang, Cheng Chen, Ruinan Jin, Baoxiang Wang, Shuai Li
   Advances in Neural Information Processing Systems (NeurIPS) 2024.
   

2. Online Control with Adversarial Disturbance for Continuous-time Linear Systems
   Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang.
   Advances in Neural Information Processing Systems (NeurIPS) 2024.
   

3. Convergence to Equilibrium of No-regret Dynamics in Congestion Games
   with Volkan Cevher, Wei Chen, Leello Dadi, Jing Dong, Ioannis Panageas, Stratis Skoulakis, Luca Viano, Siwei Wang, Jingyu Wu
   Conference on Web and Internet Economics (WINE) 2024.
   

4. Online Policy Optimization for Robust Markov Decision Process [pdf]
   with Jing Dong, Jingwei Li, Jingzhao Zhang
   Uncertainty in Artificial Intelligence (UAI) 2024.
   

5. Carbon Market Simulation with Adaptive Mechanism Design [pdf]
   Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang.
   International Joint Conference on Artificial Intelligence (IJCAI) 2024 (demonstration track).
   

6. Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games [pdf]
   Jing Dong, Baoxiang Wang, Yaoliang Yu.
   International Conference on Artificial Intelligence and Statistics (AISTATS) 2024.
   

7. On Stationary Point Convergence of PPO-Clip [pdf]
   Ruinan Jin, Shuai Li, Baoxiang Wang.
   International Conference on Learning Representations (ICLR) 2024.
   

8. Relative Policy-Transition Optimization for Fast Policy Transfer [pdf]
   Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han.
   AAAI Conference on Artificial Intelligence (AAAI) 2024.
   

9. Information Design in Multi-Agent Reinforcement Learning [pdf] [code] [talk]
   Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang.
   Advances in Neural Information Processing Systems (NeurIPS) 2023.
   

10. Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback [pdf]
    Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li.
    Advances in Neural Information Processing Systems (NeurIPS) 2023.
    

11. Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning [pdf]
    Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Long Chen, Fei Wu, Jun Xiao.
    Advances in Neural Information Processing Systems (NeurIPS) 2023.
    

12. DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning [pdf]
    Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li.
    International Joint Conference on Artificial Intelligence (IJCAI) 2023.
    

13. Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition [pdf]
    Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li.
    International Conference on Learning Representations (ICLR) 2023.
    

14. Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation [pdf]
    Jing Dong, Li Shen, Yinggan Xu, Baoxiang Wang.
    International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023 (extended abstract).
    

15. Diverse Policy Optimization for Structured Action Space [pdf]
    Wenhao Li, Baoxiang Wang, Shanchao Yang and Hongyuan Zha.
    International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023.
    

16. Online Influence Maximization under Decreasing Cascade Model [pdf]
    Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao and Shuai Li.
    International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023.
    

17. Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning [pdf]
    Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang.
    AAAI Conference on Artificial Intelligence (AAAI) 2023.
    

18. Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization [pdf]
    Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li.
    International Conference on Web Search and Data Mining (WSDM) 2023.
    

19. Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning [pdf]
    Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao
    International Conference on Machine Learning (ICML) 2022.
    

20. Cascading Bandit under Differential Privacy [pdf]
    Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li.
    International Conference on Acoustics, Speech, & Signal Processing (ICASSP) 2022.
    

21. Combinatorial Bandits under Strategic Manipulations [pdf]
    Jing Dong, Ke Li, Shuai Li, Baoxiang Wang
    International Conference on Web Search and Data Mining (WSDM) 2022.
    

22. Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning [pdf]
    Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
    Conference on Knowledge Discovery and Data Mining (KDD) 2021.
    

23. The Gambler's Problem and Beyond [pdf]
    Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan
    International Conference on Learning Representations (ICLR) 2020.
    

24. Learning and Testing Variable Partitions [pdf]
    with Andrej Bogdanov
    Innovations in Theoretical Computer Science (ITCS) 2020.
    

25. Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces [pdf][code][blog]
    Baoxiang Wang, Nidhi Hegde
    Advances in Neural Information Processing Systems (NeurIPS) 2019.
    

26. Recurrent Existence Determination Through Policy Optimization [pdf]
    International Joint Conference on Artificial Intelligence (IJCAI) 2019.
    

27. Metatrace Actor-Critic: Online Step-Size Tuning by Meta-Gradient Descent for Reinforcement Learning Control [pdf]
    Kenny Young, Baoxiang Wang, Matthew E. Taylor
    International Joint Conference on Artificial Intelligence (IJCAI) 2019.
    

28. Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning [pdf][code]
    Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng
    AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AAAI-AIIDE) 2019.
    

29. Policy Optimization with Second-Order Advantage Information [pdf][code]
    with Jiajin Li
    International Joint Conference on Artificial Intelligence (IJCAI) 2018.
    

30. Contextual Combinatorial Cascading Bandits [pdf][code]
    Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen
    International Conference on Machine Learning (ICML) 2016.
    

31. PAID: Prioritizing App Issues for Developers by Tracking User Reviews Over Versions [pdf][code]
    Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu
    International Symposium on Software Reliability Engineering (ISSRE) 2015.

Journal papers

32. Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization [pdf]
    Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li.
    Transactions on Machine Learning Research (TMLR) 2023.
    

33. Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring [pdf][code]
    Shanchao Yang, Kaili Ma, Baoxiang Wang, Tianshu Yu, Hongyuan Zha.
    Transactions on Machine Learning Research (TMLR) 2023.
    

34. Algorithms and Theory for Supervised Gradual Domain Adaptation [pdf]
    Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao.
    Transactions on Machine Learning Research (TMLR) 2022.
    

35. Learning Fair Representations via Distance Correlation Minimization [pdf]
    Dandan Guo, Chaojie Wang, Baoxiang Wang, Hongyuan Zha
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2022.