| 2025 | ICLR | Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. | Zhong Zheng, Haochen Zhang, Lingzhou Xue |
| 2025 | ICLR | Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. | Zhong Zheng, Haochen Zhang, Lingzhou Xue |
| 2025 | ICML | Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees. | Xin Yu, Zelin He, Ying Sun, Lingzhou Xue, Runze Li |
| 2025 | ICML | Gap-Dependent Bounds for Federated Q-Learning. | Haochen Zhang, Zhong Zheng, Lingzhou Xue |
| 2024 | ICLR | Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. | Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang |
| 2020 | ICPR | Improving Neural Network Robustness Through Neighborhood Preserving Layers. | Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus |
| 2017 | SDM | Discovery of Causal Time Intervals. | Zhenhui Li, Guanjie Zheng, Amal Agarwal, Lingzhou Xue, Thomas Lauvaux |
| 2007 | ICCSA | A Novel Real Time Method of Signal Strength Based Indoor Localization. | Letian Ye, Zhi Geng, Lingzhou Xue, Zhihai Liu |