Wang, Baoxiang

40 publications

ICML 2025 A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD Ruinan Jin, Xiao Li, Yaoliang Yu, Baoxiang Wang

NeurIPS 2025 ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Zeyuan Liu, Zhihe Yang, Jiawei Xu, Rui Yang, Jiafei Lyu, Baoxiang Wang, Yunjian Xu, Xiu Li

ICLR 2025 Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension Huanjian Zhou, Lingxiao Huang, Baoxiang Wang

AAAI 2025 Last-Iterate Convergence in Regularized Graphon Mean Field Game Jing Dong, Baoxiang Wang, Yaoliang Yu

ICML 2025 Learning Imperfect Information Extensive-Form Games with Last-Iterate Convergence Under Bandit Feedback Canzhe Zhao, Yutian Cheng, Jing Dong, Baoxiang Wang, Shuai Li

ICLR 2025 Learning to Communicate Through Implicit Communication Channels Han Wang, Binbin Chen, Tieying Zhang, Baoxiang Wang

AISTATS 2025 Learning to Negotiate via Voluntary Commitment Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart

AAAI 2025 Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions Canzhe Zhao, Xiangcheng Zhang, Baoxiang Wang, Shuai Li

AISTATS 2025 Multi-Agent Credit Assignment with Pretrained Language Models Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Wei Yin, Hao Shen, Bo Jin, Hongyuan Zha

ICML 2025 Reward Translation via Reward Machine in Semi-Alignable MDPs Yun Hua, Haosheng Chen, Wenhao Li, Bo Jin, Baoxiang Wang, Hongyuan Zha, Xiangfeng Wang

NeurIPS 2025 Scalable Exploration via Ensemble++ Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo

ICLRW 2025 Scalable Thompson Sampling via Ensemble++ Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo

ICLR 2025 Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling Jiawei Xu, Rui Yang, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han

NeurIPS 2025 Uncoupled and Convergent Learning in Monotone Games Under Bandit Feedback Jing Dong, Baoxiang Wang, Yaoliang Yu

IJCAI 2024 Carbon Market Simulation with Adaptive Mechanism Design Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang

AISTATS 2024 Convergence to Nash Equilibrium and No-Regret Guarantee in (Markov) Potential Games Jing Dong, Baoxiang Wang, Yaoliang Yu

NeurIPS 2024 Few-Shot Diffusion Models Escape the Curse of Dimensionality Ruofeng Yang, Bo Jiang, Cheng Chen, Ruinan Jin, Baoxiang Wang, Shuai Li

TMLR 2024 Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization Fang Kong, XiangCheng Zhang, Baoxiang Wang, Shuai Li

ICLR 2024 On Stationary Point Convergence of PPO-CLIP Ruinan Jin, Shuai Li, Baoxiang Wang

NeurIPS 2024 Online Control with Adversarial Disturbance for Continuous-Time Linear Systems Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang

UAI 2024 Online Policy Optimization for Robust Markov Decision Process Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang

AAAI 2024 Relative Policy-Transition Optimization for Fast Policy Transfer Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han

NeurIPSW 2024 Uncoupled and Convergent Learning in Monotone Games Under Bandit Feedback Jing Dong, Baoxiang Wang, Yaoliang Yu

IJCAI 2023 DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li

NeurIPS 2023 Information Design in Multi-Agent Reinforcement Learning Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang

ICLR 2023 Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li

NeurIPS 2023 Learning Adversarial Low-Rank Markov Decision Processes with Unknown Transition and Full-Information Feedback Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li

AAAI 2023 Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang

TMLR 2023 Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring Shanchao Yang, Ma Kaili, Baoxiang Wang, Tianshu Yu, Hongyuan Zha

ICMLW 2023 Online Control with Adversarial Disturbance for Continuous-Time Linear Systems Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang

NeurIPS 2023 Two Heads Are Better than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen

TMLR 2022 Algorithms and Theory for Supervised Gradual Domain Adaptation Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao

ICML 2022 Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao

NeurIPSW 2022 Online Policy Optimization for Robust MDP Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang

ICLR 2020 The Gambler's Problem and Beyond Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan

IJCAI 2019 Metatrace Actor-Critic: Online Step-Size Tuning by Meta-Gradient Descent for Reinforcement Learning Control Kenny Young, Baoxiang Wang, Matthew E. Taylor

NeurIPS 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces Baoxiang Wang, Nidhi Hegde

IJCAI 2019 Recurrent Existence Determination Through Policy Optimization Baoxiang Wang

IJCAI 2018 Policy Optimization with Second-Order Advantage Information Jiajin Li, Baoxiang Wang, Shengyu Zhang

ICML 2016 Contextual Combinatorial Cascading Bandits Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen