Yunbei Xu

Research

Submitted / Under Revision

• Pointwise Generalization in Deep Neural Networks

  with Shaojie Li.

• Upper Counterfactual Confidence Bounds: a New Optimism Principle for Contextual Bandits

  with Assaf Zeevi.

• Statistical Properties of Robust Learning under Distribution Shifts

  with Zhiyi Li, Xiaojia Mao, and Ruohan Zhan.

• Local Search with Correlated Randomness

  (with AI research assistance)

Publications

• Sampling Allocation of LinUCB: Optimal Design Limits in the Small-Gap Regime

  with Yujie Liu and Vincent Tan.

  ACM SIGMETRICS 2027.

• Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds

  with Yuzhe Yuan and Ruohan Zhan.

  Conference on Neural Information Processing Systems (NeurIPS) 2026.

  Spotlight (top 4.3%) in NeurIPS 2025 ML×OR Workshop.

• Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control

  with Yujie Liu and Vincent Tan.

  Operations Research, 2026.

  Stochastic Networks Conference Outstanding Poster Prize

• On the Power of Adaptivity for ε-Best Arm Identification in Linear Bandits

  with Arnab Maiti and Kevin Jamieson.

  Conference on Learning Theory (COLT) 2026.

• Bayesian Design Principles for Frequentist Sequential Learning

  with Assaf Zeevi.

  Journal of the ACM, 2025. Code

  International Conference on Machine Learning (ICML) 2023.

  ICML Outstanding Paper Award

  INFORMS George Nicholson Student Paper Competition, First Place

  Applied Probability Society Best Student Paper Award, Finalist

  Special Plenary Session: Highlights Beyond EC

• Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory

  with Assaf Zeevi.

  Mathematics of Operations Research, 2025.

  Applied Probability Society Best Student Paper Award, Finalist

• Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability

  with Fan Chen, Dylan Foster, Yanjun Han, Jian Qian, and Alexander Rakhlin.

  Conference on Neural Information Processing Systems (NeurIPS) 2024.

  Spotlight (top 2.5%)

  Journal version under preparation.

• Statistical Properties of Robust Satisficing

  with Zhiyi Li and Ruohan Zhan.

  International Conference on Machine Learning (ICML) 2024.

  INFORMS Undergraduate Operations Research Prize, Finalist

• Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures

  with Yanli Liu and Wotao Yin.

  Journal of Scientific Computing, 2021. Code

• Towards Problem-dependent Optimal Learning Rates

  with Assaf Zeevi.

  Conference on Neural Information Processing Systems (NeurIPS) 2020.

  Spotlight (top 4.1%)

Work in Progress

• On the Blessing of Pre-training in Weak-to-Strong Generalization

  with Wei Yao, Wang Zhaoyang, Gengze Xu, Chen Qian, Dongrui Liu, Ziqiao Wang, and Yong Liu.

• Pointwise Complexity for Gaussian Fields: Upper Envelopes, Algorithmic Lower Bounds, and Separation

  (with AI research assistance)

• Bellman-sufficient Information Complexity

  (with AI research assistance)

• In-Context Learning for Data-Driven Censored Inventory Control

  with Sohom Mukherjee, Anh-Duy Pham, and Richard Pibernik.

• Thompson Sampling for Repeated Newsvendor

  with Chen Li, Hanzhang Qin, Ruihao Zhu, and Weizhou Zhang.

• Curvature-Adaptive Doubly Robust Estimation for Continuous Treatments

  with Hongseok Namkoong and Shunri Zheng.

Professional Service and Activities

• Program Committee Service: ALT 27, COLT 24 & 26, ICLR 27, ICML 26, ISMP 27, NeurIPS 26, SIGMETRICS 27 Tutorials and Plenary Talks: EC 24, WINE 26 Professional Memberships: ACM, IMS, INFORMS