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Pan Xu

55 papers · 2016–2026 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (9) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) 🐝 Cross-Pollinator (9) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (20) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🀝 Dynamic Duo (28) πŸ‘‘ Triple Crown πŸ† Keyword Champion (3) πŸ† Grand Slam πŸ”¬ Deep Specialist (18) πŸ—ƒοΈ Keyword Collector (55) πŸ”₯ Unstoppable (10) πŸš€ Conference Pioneer ⚑ Prolific Year (8) πŸ“ˆ Trend Setter πŸ’Ž Century Club (54)

Conferences

ICML (15) NIPS (14) AAAI (9) AISTATS (6) ICLR (3) IJCAI (3) JMLR (2) UAI (2) COLT (1)

Top co-authors

Quanquan Gu (28) Tianyuan Jin (8) Xiaokui Xiao (6) Difan Zou (5) Dongruo Zhou (4) Aravind Srinivasan (4) Zhishuai Liu (4) Yifan Xu (4) Farzad Farnoud (3) Karthik Abinav Sankararaman (3)

Keywords

regret bound (8) linear programming (7) multi-armed bandit (7) variance reduction (7) nonconvex optimization (6) thompson sampling (6) online matching (5) online algorithm (4) markov chain monte carlo (4) convergence rate (4) pairwise comparison (3) stochastic gradient (3) competitive analysis (3) distributionally robust optimization (3) bipartite graph (3) sample complexity (3) reinforcement learning (3) policy gradient (3) bayesian inference (3) stochastic optimization (3)

Papers

Matching Policy Design for Gig Platforms with β€œPriority” 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