| 2025 | ICML | PILAF: Optimal Human Preference Sampling for Reward Modeling. | Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng, Julia Kempe, Yaqi Duan |
| 2023 | IJCAI | Invertible Residual Neural Networks with Conditional Injector and Interpolator for Point Cloud Upsampling. | Aihua Mao, Yaqi Duan, Yu-Hui Wen, Zihui Du, Hongmin Cai, Yong-Jin Liu |
| 2022 | ICLR | Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. | Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang |
| 2021 | ICML | Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning. | Yaqi Duan, Chi Jin, Zhiyuan Li |
| 2021 | ICML | Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. | Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvri, Mengdi Wang |
| 2021 | ICML | Bootstrapping Fitted Q-Evaluation for Off-Policy Inference. | Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvri, Mengdi Wang |
| 2021 | ISIT | Learning Good State and Action Representations via Tensor Decomposition. | Chengzhuo Ni, Anru R. Zhang, Yaqi Duan, Mengdi Wang |
| 2020 | ICML | Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation. | Yaqi Duan, Zeyu Jia, Mengdi Wang |