Baoxiang Wang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 61

Top Topics

Markov Decision Process

Nash Equilibrium

Reinforcement Learning

Influence Maximization

Top Venues

Publications

Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. Trans. Mach. Learn. Res. 2024 (2024)
Jiawei Xu, Rui Yang, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han
Robust Decision Transformer: Tackling Data Corruption in Offline RL via Sequence Modeling. CoRR (2024)
Jing Dong, Baoxiang Wang, Yaoliang Yu
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games. AISTATS (2024)
Jing Dong, Baoxiang Wang, Yaoliang Yu
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games. CoRR (2024)
Dandan Guo, Chaojie Wang, Baoxiang Wang, Hongyuan Zha
Learning Fair Representations via Distance Correlation Minimization. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang
Carbon Market Simulation with Adaptive Mechanism Design. CoRR (2024)
Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han
Relative Policy-Transition Optimization for Fast Policy Transfer. AAAI (2024)
Ruinan Jin, Shuai Li, Baoxiang Wang
On Stationary Point Convergence of PPO-Clip. ICLR (2024)
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. CoRR (2023)
Jing Dong, Jingyu Wu, Siwei Wang, Baoxiang Wang, Wei Chen
Taming the Exponential Action Set: Sublinear Regret and Fast Convergence to Nash Equilibrium in Online Congestion Games. CoRR (2023)
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition. ICLR (2023)
Wenhao Li, Baoxiang Wang, Shanchao Yang, Hongyuan Zha
Diverse Policy Optimization for Structured Action Space. CoRR (2023)
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. CoRR (2023)
Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
Online Influence Maximization under Decreasing Cascade Model. AAMAS (2023)
Shanchao Yang, Kaili Ma, Baoxiang Wang, Tianshu Yu, Hongyuan Zha
Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring. Trans. Mach. Learn. Res. 2023 (2023)
Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning. NeurIPS (2023)
Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang
Information Design in Multi-Agent Reinforcement Learning. NeurIPS (2023)
Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang
Information Design in Multi-Agent Reinforcement Learning. CoRR (2023)
Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning. AAAI (2023)
Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang
Online Control with Adversarial Disturbance for Continuous-time Linear Systems. CoRR (2023)
Jing Dong, Li Shen, Yinggan Xu, Baoxiang Wang
Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. AAMAS (2023)
Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Bo Jin, Hongyuan Zha
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning. CoRR (2023)
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. IJCAI (2023)
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. NeurIPS (2023)
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. WSDM (2023)
Wenhao Li, Baoxiang Wang, Shanchao Yang, Hongyuan Zha
Diverse Policy Optimization for Structured Action Space. AAMAS (2023)
Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. CoRR (2023)
Fang Kong, Jize Xie, Baoxiang Wang, Tao Yao, Shuai Li
Online Influence Maximization under Decreasing Cascade Model. CoRR (2023)
Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li
Cascading Bandit Under Differential Privacy. ICASSP (2022)
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
Algorithms and Theory for Supervised Gradual Domain Adaptation. Trans. Mach. Learn. Res. 2022 (2022)
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao
Algorithms and Theory for Supervised Gradual Domain Adaptation. CoRR (2022)
Jing Dong, Ke Li, Shuai Li, Baoxiang Wang
Combinatorial Bandits under Strategic Manipulations. WSDM (2022)
Jing Dong, Li Shen, Yinggan Xu, Baoxiang Wang
Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. CoRR (2022)
Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning. ICML (2022)
Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
Online Policy Optimization for Robust MDP. CoRR (2022)
Canzhe Zhao, Yanjie Ze, Jing Dong, Baoxiang Wang, Shuai Li
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. CoRR (2022)
Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang
Learning From Good Trajectories in Offline Multi-Agent Reinforcement Learning. CoRR (2022)
Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao
Cascading Bandit under Differential Privacy. CoRR (2021)
Jing Dong, Ke Li, Shuai Li, Baoxiang Wang
Combinatorial Bandits under Strategic Manipulations. CoRR (2021)
Baoxiang Wang, Huanjian Zhou
Multilinear extension of k-submodular functions. CoRR (2021)
Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. KDD (2021)
Qi Tian, Kun Kuang, Baoxiang Wang, Furui Liu, Fei Wu
Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth. CoRR (2021)
Shanchao Yang, Kaili Ma, Baoxiang Wang, Hongyuan Zha
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient. CoRR (2021)
Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. CoRR (2021)
Jing Dong, Shuai Li, Baoxiang Wang
Incentivizing an Unknown Crowd. CoRR (2021)
Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan
The Gambler's Problem and Beyond. ICLR (2020)
Andrej Bogdanov, Baoxiang Wang
Learning and Testing Variable Partitions. ITCS (2020)
Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan
The Gambler's Problem and Beyond. CoRR (2020)
Andrej Bogdanov, Baoxiang Wang
Learning and Testing Variable Partitions. CoRR (2020)
Baoxiang Wang
Recurrent Existence Determination Through Policy Optimization. CoRR (2019)
Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng
Beyond Winning and Losing: Modeling Human Motivations and Behaviors with Vector-Valued Inverse Reinforcement Learning. AIIDE (2019)
Baoxiang Wang, Nidhi Hegde
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces. NeurIPS (2019)
Baoxiang Wang, Nidhi Hegde
Private Q-Learning with Functional Noise in Continuous Spaces. CoRR (2019)
Baoxiang Wang
Recurrent Existence Determination Through Policy Optimization. IJCAI (2019)
Kenny Young, Baoxiang Wang, Matthew E. Taylor
Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control. IJCAI (2019)
Jiajin Li, Baoxiang Wang
Policy Optimization with Second-Order Advantage Information. ICLR (Workshop) (2018)
Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng
Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning. CoRR (2018)
Kenny Young, Baoxiang Wang, Matthew E. Taylor
Metatrace: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control. CoRR (2018)
Jiajin Li, Baoxiang Wang
Policy Optimization with Second-Order Advantage Information. CoRR (2018)
Jiajin Li, Baoxiang Wang, Shengyu Zhang
Policy Optimization with Second-Order Advantage Information. IJCAI (2018)
Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen
Contextual Combinatorial Cascading Bandits. ICML (2016)
Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu
PAID: Prioritizing app issues for developers by tracking user reviews over versions. ISSRE (2015)