| Zeyu Shen, Zhiyi Wang, Xingyu Zhu, Brandon Fain, and Kamesh Munagala. Fairness in the Assignment Problem with Uncertain Priorities. (AAMAS'23) | |
| Youzhi Zhang, Bo An, and V.S. Subrahmanian. Computing Optimal Nash Equilibria in Multiplayer Games. (NeurIPS'23) | |
| Tianyi Zhang, Junyu Zhang, Sizhe Gu, and Dengji Zhao. Cost Sharing under Private Valuation and Connection Control. (AAMAS'23) |
| Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, and Xian Fu. RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution. (ICML'23) | |
| Xihuai Wang, Zheng Tian, Ziyu Wan, Ying Wen, Jun Wang, and Weinan Zhang. Order Matters: Agent-by-agent Policy Optimization. (ICLR'23) | |
| Yang Li*, Shao Zhang*, Jichen Sun, Yali Du, Ying Wen, Xinbing Wang, and Wei Pan. Cooperative Open-ended Learning Framework for Zero-Shot Coordination. (ICML'23) | |
| Fuxiang Zhang*, Chengxing Jia*, Yi-Chen Li, Lei Yuan, Yang Yu, Zongzhang Zhang. Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data. (ICLR'23) | |
| Yang Chen, Libo Zhang, Jiamou Liu, and Michael Witbrock. Adversarial Inverse Reinforcement Learning for Mean Field Games. (AAMAS'23) |
| Junjie Sheng, Lu Wang, Fangkai Yang, Bo Qiao, Hang Dong, Xiangfeng Wang, Bo Jin, Jun Wang, Si Qin, Saravan Rajmohan, Qingwei Lin, and Dongmei Zhang. Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning. (WWW'23) | |
| Yue Hu, Yifan Lu, Runsheng Xu, Weidi Xie, Siheng Chen, and Yanfeng Wang. Collaboration Helps Camera Overtake LiDAR in 3D Detection. (CVPR'23) | |
| Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, and Siheng Chen. Where2comm: Communication-efficient Collaborative Perception via Spatial Confidence Maps. (NeurIPS'22) |
| Jiacheng Xu, Chao Chen, Fuxiang Zhang, Lei Yuan, Zongzhang Zhang, and Yang Yu. Internal Logical Induction for Pixel-Symbolic Reinforcement Learning. (KDD'23) |
| Weirui Ye*, Yunsheng Zhang*, Pieter Abbeel, Yang Gao. Become a Proficient Player with Limited Data through Watching Pure Videos. (ICLR'23) | |
| Yingdong Hu, Renhao Wang, Li Erran Li, and Yang Gao. For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal. (ICML'23) | |
| Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Haifeng Zhang, and Weinan Zhang. Large Sequence Models for Sequential Decision-making: A Survey. (Frontiers of Computer Science 17, 6, Article 176349) | |
| Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, and Luo Mai. GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. (ICML'23) |
| Yihao Sun, Jiaji Zhang, Chengxing Jia, Haoxin Lin, Junyin Ye, and Yang Yu. Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning. (ICML'23) | |
| Yi Ma, Hongyao Tang, Dong Li, and Zhaopeng Meng. Reining Generalization in Offline Reinforcement Learning via Representation Distinction. (NeurIPS'23) | |
| Yuhang Ran, Yi-Chen Li, Fuxiang Zhang, Zongzhang Zhang, and Yang Yu. Policy Regularization with Dataset Constraint for Offline Reinforcement Learning. (ICML'23) | |
| Jialei Huang, Zhao-Heng Yin, Yingdong Hu, and Yang Gao. Policy Contrastive Imitation Learning. (ICML'23) |
| Junru Zhang, Lang Feng, Haowen Zhang, Yuhan Wu, and Yabo Dong. Adacket: ADAptive Convolutional KErnel Transform for Multivariate Time Series Classification. (ECML/PKDD'23) | |
| Fei Ni, Jianye Hao, Yao Mu, Yifu Yuan, Yan Zheng, Bin Wang, and Zhixuan Liang. MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL. (ICML'23) |
| Tong Zhang, Yingdong Hu, Hanchen Cui, Hang Zhao, and Yang Gao. A Universal Semantic-Geometric Representation for Robotic Manipulation. (CoRL'23) | |
| Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, Yan Zheng, Yujing Hu, Jinyi Liu, Yingfeng Chen, Changjie Fan. EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model. (ICLR'23) | |
| Hebin Liang, Zibin Dong, Yi Ma, Xiaotian Hao, Yan Zheng, and Jianye Hao. A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving. (CIKM'23) |