Pan Xu

Matching Policy Design for Gig Platforms with “Priority” Features AAAI 2026 Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction ICML 2025 Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization ICML 2025 Optimal Batched Linear Bandits ICML 2024 Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NIPS 2024 Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions NIPS 2024 Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NIPS 2024 Optimal Batched Best Arm Identification NIPS 2024 Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation NIPS 2024 Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs AAAI 2024 Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo ICLR 2024 Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation ICML 2024 Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations ICML 2024 Design a Win-Win Strategy That Is Fair to Both Service Providers and Tasks When Rejection Is Not an Option IJCAI 2024 Equity Promotion in Public Transportation AAAI 2023 Thompson Sampling with Less Exploration is Fast and Optimal ICML 2023 Distributionally Robust Policy Gradient for Offline Contextual Bandits AISTATS 2023 Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons AISTATS 2022 Equity Promotion in Online Resource Allocation AAAI 2022 Langevin Monte Carlo for Contextual Bandits ICML 2022 Neural Contextual Bandits with Deep Representation and Shallow Exploration ICLR 2022 Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits NIPS 2022 Active Ranking without Strong Stochastic Transitivity NIPS 2022 MOTS: Minimax Optimal Thompson Sampling ICML 2021 Double Explore-then-Commit: Asymptotic Optimality and Beyond COLT 2021 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits ICML 2021 Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling UAI 2021 Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours AAAI 2020 Stochastic Nested Variance Reduction for Nonconvex Optimization JMLR 2020 A Unified Model for the Two-stage Offline-then-Online Resource Allocation IJCAI 2020 Trade the System Efficiency for the Income Equality of Drivers in Rideshare IJCAI 2020 A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation ICML 2020 A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods NIPS 2020 Rank Aggregation via Heterogeneous Thurstone Preference Models AAAI 2020 Sample Efficient Policy Gradient Methods with Recursive Variance Reduction ICLR 2020 A Unified Approach to Online Matching with Conflict-Aware Constraints AAAI 2019 Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach AAAI 2019 Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics AISTATS 2019 Stochastic Variance-Reduced Cubic Regularization Methods JMLR 2019 An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient UAI 2019 Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NIPS 2019 Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity AAAI 2019 Stochastic Nested Variance Reduction for Nonconvex Optimization NIPS 2018 Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018 Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018 Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions ICML 2018 Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization ICML 2018 Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima NIPS 2018 Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms AISTATS 2018 Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization NIPS 2018 Efficient Algorithm for Sparse Tensor-variate Gaussian Graphical Models via Gradient Descent AISTATS 2017 Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization NIPS 2017 Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference ICML 2017 Semiparametric Differential Graph Models NIPS 2016