| 2026 | AAAI | Matching Policy Design for Gig Platforms with "Priority" Features. | Evan Yifan Xu, Pan Xu |
| 2025 | ICML | Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction. | Yiting He, Zhishuai Liu, Weixin Wang, Pan Xu |
| 2025 | ICML | Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization. | Cheng Tang, Zhishuai Liu, Pan Xu |
| 2024 | AAAI | Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs. | Tianyuan Jin, Hao-Lun Hsu, William Chang, Pan Xu |
| 2024 | AISTATS | Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation. | Zhishuai Liu, Pan Xu |
| 2024 | ICLR | Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. | Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli |
| 2024 | ICML | Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations. | Pan Xu |
| 2024 | ICML | Optimal Batched Linear Bandits. | Xuanfei Ren, Tianyuan Jin, Pan Xu |
| 2024 | ICML | Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation. | Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu |
| 2024 | IJCAI | Design a Win-Win Strategy That Is Fair to Both Service Providers and Tasks When Rejection Is Not an Option. | Yohai Trabelsi, Pan Xu, Sarit Kraus |
| 2024 | WWW | Tight Competitive and Variance Analyses of Matching Policies in Gig Platforms. | Pan Xu |
| 2023 | AAAI | Equity Promotion in Public Transportation. | Anik Pramanik, Pan Xu, Yifan Xu |
| 2023 | AISTATS | Distributionally Robust Policy Gradient for Offline Contextual Bandits. | Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar |
| 2023 | ICML | Thompson Sampling with Less Exploration is Fast and Optimal. | Tianyuan Jin, Xianglin Yang, Xiaokui Xiao, Pan Xu |
| 2023 | SIGMETRICS | Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. | Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman |
| 2022 | AAAI | Equity Promotion in Online Resource Allocation. | Pan Xu, Yifan Xu |
| 2022 | AISTATS | Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons. | Yue Wu, Tao Jin, Hao Lou, Pan Xu, Farzad Farnoud, Quanquan Gu |
| 2022 | ICLR | Neural Contextual Bandits with Deep Representation and Shallow Exploration. | Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu |
| 2022 | ICML | Langevin Monte Carlo for Contextual Bandits. | Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar |
| 2021 | COLT | Double Explore-then-Commit: Asymptotic Optimality and Beyond. | Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu |
| 2021 | ICML | MOTS: Minimax Optimal Thompson Sampling. | Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu |
| 2021 | ICML | Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits. | Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu |
| 2021 | UAI | Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling. | Difan Zou, Pan Xu, Quanquan Gu |
| 2020 | AAAI | Rank Aggregation via Heterogeneous Thurstone Preference Models. | Tao Jin, Pan Xu, Quanquan Gu, Farzad Farnoud |
| 2020 | AAAI | Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. | Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan |
| 2020 | AIES | Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. | Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan |
| 2020 | ICLR | Sample Efficient Policy Gradient Methods with Recursive Variance Reduction. | Pan Xu, Felicia Gao, Quanquan Gu |
| 2020 | ICML | A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation. | Pan Xu, Quanquan Gu |
| 2020 | IJCAI | A Unified Model for the Two-stage Offline-then-Online Resource Allocation. | Yifan Xu, Pan Xu, Jianping Pan, Jun Tao |
| 2020 | IJCAI | Trade the System Efficiency for the Income Equality of Drivers in Rideshare. | Yifan Xu, Pan Xu |
| 2019 | AAAI | Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. | John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu |
| 2019 | AAAI | A Unified Approach to Online Matching with Conflict-Aware Constraints. | Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas |
| 2019 | AAAI | Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach. | Boming Zhao, Pan Xu, Yexuan Shi, Yongxin Tong, Zimu Zhou, Yuxiang Zeng |
| 2019 | AISTATS | Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics. | Difan Zou, Pan Xu, Quanquan Gu |
| 2019 | ICDE | Interaction-Aware Arrangement for Event-Based Social Networks. | Feifei Kou, Zimu Zhou, Hao Cheng, Junping Du, Yexuan Shi, Pan Xu |
| 2019 | ICDE | Adaptive Dynamic Bipartite Graph Matching: A Reinforcement Learning Approach. | Yansheng Wang, Yongxin Tong, Cheng Long, Pan Xu, Ke Xu, Weifeng Lv |
| 2019 | UAI | An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient. | Pan Xu, Felicia Gao, Quanquan Gu |
| 2018 | AAAI | Allocation Problems in Ride-Sharing Platforms: Online Matching With Offline Reusable Resources. | John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu |
| 2018 | AISTATS | Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms. | Pan Xu, Tianhao Wang, Quanquan Gu |
| 2018 | ICA3PP | A Secure and Targeted Mobile Coupon Delivery Scheme Using Blockchain. | Yingjie Gu, Xiaolin Gui, Pan Xu, Ruowei Gui, Yingliang Zhao, Wenjie Liu |
| 2018 | ICALP | A PTAS for a Class of Stochastic Dynamic Programs. | Hao Fu, Jian Li, Pan Xu |
| 2018 | ICDE | Onion Curve: A Space Filling Curve with Near-Optimal Clustering. | Pan Xu, Cuong Nguyen, Srikanta Tirthapura |
| 2018 | ICML | Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization. | Jinghui Chen, Pan Xu, Lingxiao Wang, Jian Ma, Quanquan Gu |
| 2018 | ICML | Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions. | Pan Xu, Tianhao Wang, Quanquan Gu |
| 2018 | ICML | Stochastic Variance-Reduced Cubic Regularized Newton Method. | Dongruo Zhou, Pan Xu, Quanquan Gu |
| 2018 | ICML | Stochastic Variance-Reduced Hamilton Monte Carlo Methods. | Difan Zou, Pan Xu, Quanquan Gu |
| 2018 | SODA | Algorithms to Approximate Column-Sparse Packing Problems. | Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu |
| 2018 | UAI | Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics. | Difan Zou, Pan Xu, Quanquan Gu |
| 2017 | AISTATS | Efficient Algorithm for Sparse Tensor-variate Gaussian Graphical Models via Gradient Descent. | Pan Xu, Tingting Zhang, Quanquan Gu |
| 2017 | ICML | Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference. | Aditya Chaudhry, Pan Xu, Quanquan Gu |
| 2016 | ESA | New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching. | Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu |
| 2016 | UAI | Forward Backward Greedy Algorithms for Multi-Task Learning with Faster Rates. | Lu Tian, Pan Xu, Quanquan Gu |
| 2015 | ICDE | Mining maximal cliques from an uncertain graph. | Arko Provo Mukherjee, Pan Xu, Srikanta Tirthapura |
| 2012 | PODS | On the optimality of clustering properties of space filling curves. | Pan Xu, Srikanta Tirthapura |