Publications
You can also find my articles on my Google Scholar profile.
Preprints
- Zhang, H., Xue, L., and Zheng, Z. (2026). Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning.
- Zhang, H., Zheng, Z., and Xue, L. (2026). Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation.
- Song, C., Zheng, Z., Li, B., and Xue, L. (2025). Collapsing Categories for Regression with Mixed Predictors.
- Zheng, Z., Chen, Q., Fang, E. X., and Shi, C. (2024+). Online Learning for Inventory Control Problems under Random Yield.
- Zheng, Z. and Xue, L. (2024+). Smoothed Robust Phase Retrieval.
- Zheng, Z., Aybat, N. S., Ma, S., and Xue, L. (2024+). Adaptive Algorithms for Robust Phase Retrieval. SIAM Journal on Optimization, under review.
Publications
- Zheng, Z., Yu, X., Ma, S., and Xue, L. (2026). A New Inexact Manifold Proximal Linear Algorithm with Adaptive Stopping Criteria. INFORMS Journal on Optimization, in press.
- Zhang, H., Zheng, Z. (co-first author), and Xue, L. (2026). Q-Learning with Fine-Grained Gap-Dependent Regret. The Fourteenth International Conference on Learning Representations (ICLR).
- Zhang, H., Zheng, Z. (co-first author), and Xue, L. (2025). Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning. The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS).
- Zhang, H., Zheng, Z. (co-first author), and Xue, L. (2025). Gap-Dependent Bounds for Federated Q-Learning. The Forty-Second International Conference on Machine Learning (ICML).
- Zheng, Z., Zhang, H. (co-first author), and Xue, L. (2025). Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. The Thirteenth International Conference on Learning Representations (ICLR), Spotlight.
- Zheng, Z., Zhang, H. (co-first author), and Xue, L. (2025). Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. The Thirteenth International Conference on Learning Representations (ICLR).
- Zheng, Z., Gao, F., Xue, L., and Yang, J. (2024). Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. The Twelfth International Conference on Learning Representations (ICLR).
- Zheng, Z., Ma, S., and Xue, L. (2024). A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval. IEEE Transactions on Signal Processing, 72, 1081–1093.
- Shaheena, S. W., Wen, T., Zheng, Z., Xue, L., Baka, J., and Brantley, S. L. (2024). Wastewaters Co-Produced with Shale Gas Drive Slight Regional Salinization of Groundwater. Environmental Science & Technology, 58, 17862–17873.