Xue, Lingzhou

10 publications

NeurIPS 2025 AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections Xin Yu, Yujia Wang, Jinghui Chen, Lingzhou Xue

ICLR 2025 Federated $q$-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost Zhong Zheng, Haochen Zhang, Lingzhou Xue

ICML 2025 Gap-Dependent Bounds for Federated $q$-Learning Haochen Zhang, Zhong Zheng, Lingzhou Xue

ICLR 2025 Gap-Dependent Bounds for Q-Learning Using Reference-Advantage Decomposition Zhong Zheng, Haochen Zhang, Lingzhou Xue

NeurIPS 2025 Regret-Optimal Q-Learning with Low Cost for Single-Agent and Federated Reinforcement Learning Haochen Zhang, Zhong Zheng, Lingzhou Xue

NeurIPS 2025 Stability and Oracle Inequalities for Optimal Transport Maps Between General Distributions Shubo Li, Yizhe Ding, Lingzhou Xue, Runze Li

ICML 2025 Understanding the Statistical Accuracy-Communication Trade-Off in Personalized Federated Learning with Minimax Guarantees Xin Yu, Zelin He, Ying Sun, Lingzhou Xue, Runze Li

ICLR 2024 Federated Q-Learning: Linear Regret Speedup with Low Communication Cost Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang

JMLR 2022 Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold Bokun Wang, Shiqian Ma, Lingzhou Xue

PGM 2020 Hawkesian Graphical Event Models Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue