PAID: Prioritizing app issues for developers by tracking user reviews over versions. - Cuiyun Gao 001; Baoxiang Wang 001; Pinjia He; Jieming Zhu; Yangfan Zhou; Michael R. Lyu (ISSRE, 2015)

Contextual Combinatorial Cascading Bandits. - Shuai Li 010; Baoxiang Wang 001; Shengyu Zhang 002; Wei Chen 013 (ICML, 2016)

Policy Optimization with Second-Order Advantage Information. - Jiajin Li; Baoxiang Wang 001 (ICLR (Workshop), 2018)

Policy Optimization with Second-Order Advantage Information. - Jiajin Li; Baoxiang Wang 001; Shengyu Zhang 002 (IJCAI, 2018)

Metatrace: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control. - Kenny Young; Baoxiang Wang 001; Matthew E. Taylor (CoRR, 2018)

Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning. - Baoxiang Wang 001; Tongfang Sun; Xianjun Sam Zheng (CoRR, 2018)

Beyond Winning and Losing: Modeling Human Motivations and Behaviors with Vector-Valued Inverse Reinforcement Learning. - Baoxiang Wang 001; Tongfang Sun; Xianjun Sam Zheng (AIIDE, 2019)

Recurrent Existence Determination Through Policy Optimization. - Baoxiang Wang 001 (IJCAI, 2019)

Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control. - Kenny Young; Baoxiang Wang 001; Matthew E. Taylor (IJCAI, 2019)

Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces. - Baoxiang Wang 001; Nidhi Hegde 001 (NeurIPS, 2019)

Private Q-Learning with Functional Noise in Continuous Spaces. - Baoxiang Wang 001; Nidhi Hegde 001 (CoRR, 2019)

The Gambler's Problem and Beyond. - Baoxiang Wang 001; Shuai Li 010; Jiajin Li; Siu On Chan (ICLR, 2020)

Learning and Testing Variable Partitions. - Andrej Bogdanov; Baoxiang Wang 001 (ITCS, 2020)

Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. - Jiahui Li 003; Kun Kuang; Baoxiang Wang 001; Furui Liu; Long Chen 016; Fei Wu 001; Jun Xiao 001 (KDD, 2021)

Cascading Bandit under Differential Privacy. - Kun Wang; Jing Dong 008; Baoxiang Wang 001; Shuai Li 010; Shuo Shao (CoRR, 2021)

Multilinear extension of k-submodular functions. - Baoxiang Wang 001; Huanjian Zhou (CoRR, 2021)

Incentivizing an Unknown Crowd. - Jing Dong 008; Shuai Li 010; Baoxiang Wang 001 (CoRR, 2021)

Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient. - Shanchao Yang; Kaili Ma 001; Baoxiang Wang 001; Hongyuan Zha (CoRR, 2021)

Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth. - Qi Tian 001; Kun Kuang; Baoxiang Wang 001; Furui Liu; Fei Wu 001 (CoRR, 2021)

Cascading Bandit Under Differential Privacy. - Kun Wang; Jing Dong 008; Baoxiang Wang 001; Shuai Li 010 (ICASSP, 2022)

Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning. - Jiahui Li 003; Kun Kuang; Baoxiang Wang 001; Furui Liu; Long Chen 016; Changjie Fan; Fei Wu 001; Jun Xiao 001 (ICML, 2022)

Combinatorial Bandits under Strategic Manipulations. - Jing Dong 008; Ke Li; Shuai Li 010; Baoxiang Wang 001 (WSDM, 2022)

Online Policy Optimization for Robust MDP. - Jing Dong 008; Jingwei Li; Baoxiang Wang 001; Jingzhao Zhang (CoRR, 2022)

Algorithms and Theory for Supervised Gradual Domain Adaptation. - Jing Dong 008; Shiji Zhou; Baoxiang Wang 001; Han Zhao 002 (Trans. Mach. Learn. Res., 2022)

Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning. - Qi Tian 001; Kun Kuang; Furui Liu; Baoxiang Wang 001 (AAAI, 2023)

Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. - Jing Dong 008; Li Shen 008; Yinggan Xu; Baoxiang Wang 001 (AAMAS, 2023)

Online Influence Maximization under Decreasing Cascade Model. - Fang Kong 002; Jize Xie; Baoxiang Wang 001; Tao Yao; Shuai Li 010 (AAMAS, 2023)

Diverse Policy Optimization for Structured Action Space. - Wenhao Li 001; Baoxiang Wang 001; Shanchao Yang; Hongyuan Zha (AAMAS, 2023)

Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition. - Canzhe Zhao; Ruofeng Yang; Baoxiang Wang 001; Shuai Li 010 (ICLR, 2023)

DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning. - Canzhe Zhao; Yanjie Ze; Jing Dong 008; Baoxiang Wang 001; Shuai Li 010 (IJCAI, 2023)

Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning. - Jiahui Li 003; Kun Kuang; Baoxiang Wang 001; Xingchen Li; Fei Wu 001; Jun Xiao 001; Long Chen 016 (NeurIPS, 2023)

Information Design in Multi-Agent Reinforcement Learning. - Yue Lin; Wenhao Li 001; Hongyuan Zha; Baoxiang Wang 001 (NeurIPS, 2023)

Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. - Canzhe Zhao; Ruofeng Yang; Baoxiang Wang 001; Xuezhou Zhang; Shuai Li 010 (NeurIPS, 2023)

Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization. - Canzhe Zhao; Yanjie Ze; Jing Dong 008; Baoxiang Wang 001; Shuai Li 010 (WSDM, 2023)

Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning. - Wenhao Li 001; Dan Qiao; Baoxiang Wang 001; Xiangfeng Wang; Bo Jin 003; Hongyuan Zha (CoRR, 2023)

Online Control with Adversarial Disturbance for Continuous-time Linear Systems. - Jingwei Li; Jing Dong 008; Baoxiang Wang 001; Jingzhao Zhang (CoRR, 2023)

Taming the Exponential Action Set: Sublinear Regret and Fast Convergence to Nash Equilibrium in Online Congestion Games. - Jing Dong 008; Jingyu Wu; Siwei Wang 002; Baoxiang Wang 001; Wei Chen 020 (CoRR, 2023)

Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring. - Shanchao Yang; Kaili Ma 001; Baoxiang Wang 001; Tianshu Yu 001; Hongyuan Zha (Trans. Mach. Learn. Res., 2023)

Relative Policy-Transition Optimization for Fast Policy Transfer. - Jiawei Xu; Cheng Zhou; Yizheng Zhang; Baoxiang Wang 001; Lei Han 001 (AAAI, 2024)

Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games. - Jing Dong 008; Baoxiang Wang 001; Yaoliang Yu (AISTATS, 2024)

On Stationary Point Convergence of PPO-Clip. - Ruinan Jin; Shuai Li 010; Baoxiang Wang 001 (ICLR, 2024)

Carbon Market Simulation with Adaptive Mechanism Design. - Han Wang; Wenhao Li 001; Hongyuan Zha; Baoxiang Wang 001 (IJCAI, 2024)

Online Control with Adversarial Disturbance for Continuous-time Linear Systems. - Jingwei Li; Jing Dong 008; Can Chang; Baoxiang Wang 001; Jingzhao Zhang (NeurIPS, 2024)

Few-Shot Diffusion Models Escape the Curse of Dimensionality. - Ruofeng Yang; Bo Jiang; Cheng Chen 015; Ruinan Jin; Baoxiang Wang 001; Shuai Li 010 (NeurIPS, 2024)

Online Policy Optimization for Robust Markov Decision Process. - Jing Dong 008; Jingwei Li; Baoxiang Wang 001; Jingzhao Zhang (UAI, 2024)

Robust Decision Transformer: Tackling Data Corruption in Offline RL via Sequence Modeling. - Jiawei Xu; Rui Yang 010; Feng Luo; Meng Fang; Baoxiang Wang 001; Lei Han 001 (CoRR, 2024)

Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback. - Jing Dong 008; Baoxiang Wang 001; Yaoliang Yu (CoRR, 2024)

Adaptive complexity of log-concave sampling. - Huanjian Zhou; Baoxiang Wang 001; Masashi Sugiyama (CoRR, 2024)

Asymptotic and Non-Asymptotic Convergence Analysis of AdaGrad for Non-Convex Optimization via Novel Stopping Time-based Analysis. - Ruinan Jin; Xiaoyu Wang; Baoxiang Wang 001 (CoRR, 2024)

A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD. - Ruinan Jin; Xiao Li; Yaoliang Yu; Baoxiang Wang 001 (CoRR, 2024)

Learning to Construct Implicit Communication Channel. - Han Wang; Binbin Chen; Tieying Zhang; Baoxiang Wang 001 (CoRR, 2024)

On the Decomposition of Differential Game. - Nanxiang Zhou; Jing Dong 008; Yutian Li; Baoxiang Wang 001 (CoRR, 2024)

Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. - Fang Kong 002; Xiangcheng Zhang; Baoxiang Wang 001; Shuai Li 010 (Trans. Mach. Learn. Res., 2024)

Learning Fair Representations via Distance Correlation Minimization. - Dandan Guo; Chaojie Wang 001; Baoxiang Wang 001; Hongyuan Zha (IEEE Trans. Neural Networks Learn. Syst., 2024)

Last-iterate Convergence in Regularized Graphon Mean Field Game. - Jing Dong 008; Baoxiang Wang 001; Yaoliang Yu (AAAI, 2025)

Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions. - Canzhe Zhao; Xiangcheng Zhang; Baoxiang Wang 001; Shuai Li 010 (AAAI, 2025)

Multi-Agent Credit Assignment with Pretrained Language Models. - Wenhao Li 001; Dan Qiao; Baoxiang Wang 001; Xiangfeng Wang; Wei Yin; Hao Shen 002; Bo Jin 003; Hongyuan Zha (AISTATS, 2025)

Learning to Negotiate via Voluntary Commitment. - Shuhui Zhu; Baoxiang Wang 001; Sriram Ganapathi Subramanian; Pascal Poupart (AISTATS, 2025)

Learning to Communicate Through Implicit Communication Channels. - Han Wang; Binbin Chen; Tieying Zhang; Baoxiang Wang 001 (ICLR, 2025)

Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling. - Jiawei Xu; Rui Yang 010; Shuang Qiu; Feng Luo; Meng Fang; Baoxiang Wang 001; Lei Han 001 (ICLR, 2025)

The adaptive complexity of parallelized log-concave sampling. - Huanjian Zhou; Baoxiang Wang 001; Masashi Sugiyama (ICLR, 2025)

Improved Approximation Algorithms for k-Submodular Maximization via Multilinear Extension. - Huanjian Zhou; Lingxiao Huang; Baoxiang Wang 001 (ICLR, 2025)

Verbalized Bayesian Persuasion. - Wenhao Li 001; Yue Lin; Xiangfeng Wang; Bo Jin 003; Hongyuan Zha; Baoxiang Wang 001 (CoRR, 2025)

Offline Multi-agent Reinforcement Learning via Score Decomposition. - Dan Qiao; Wenhao Li 001; Shanchao Yang; Hongyuan Zha; Baoxiang Wang 001 (CoRR, 2025)

Pointwise Convergence in Games with Conflicting Interest. - Nanxiang Zhou; Jing Dong 008; Baoxiang Wang 001 (CoRR, 2025)

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning. - Zeyuan Liu; Zhihe Yang; Jiawei Xu; Rui Yang 010; Jiafei Lyu; Baoxiang Wang 001; Yunjian Xu; Xiu Li 001 (CoRR, 2025)

Information Bargaining: Bilateral Commitment in Bayesian Persuasion. - Yue Lin; Shuhui Zhu; William A Cunningham; Wenhao Li 001; Pascal Poupart; Hongyuan Zha; Baoxiang Wang 001 (CoRR, 2025)

Reinforcement Learning for Target Zone Blood Glucose Control. - David H. Mguni; Jing Dong 008; Wanrong Yang; Ziquan Liu; Muhammad Salman Haleem; Baoxiang Wang 001 (CoRR, 2025)