1 citations · 2 across the 7 of their papers we have counts for
8 papers
Sampling Allocation of LinUCB: Optimal Design Limits in the Small-Gap Regime
Yujie Liu, Vincent Y. F. Tan, Yunbei Xu
We study the sampling allocation of LinUCB in the small-gap regime, where the reward gaps are of order at most over the decision horizon . This scaling captures the h…
Statistical Properties of Robust Learning under Distributional Shifts
Zhiyi Li, Xiaojie Mao, Yunbei Xu +1
Distributional shifts arise when the target deployment environment differs from the source environment that generated the training data. Robust learning frameworks such as Distribu…
In-Context Learning for Data-Driven Censored Inventory Control
Sohom Mukherjee, Anh-Duy Pham, Richard Pibernik +1
We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determines whether demand is fully o…
Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds
Yunbei Xu, Yuzhe Yuan, Ruohan Zhan
We study the fundamental and timely problem of learning long sequences in autoregressive modeling and next-token prediction under model misspecification, measured by the joint Kull…
Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control
Yujie Liu, Vincent Y. F. Tan, Yunbei Xu
We introduce an original minimax framework for finite-time performance analysis in queueing control and propose a surprisingly simple Lyapunov-based scheduling policy with superior…
Thompson Sampling for Repeated Newsvendor
Li Chen, Hanzhang Qin, Yunbei Xu +2
In this paper, we investigate the performance of Thompson Sampling (TS) for online learning with censored feedback, focusing primarily on the classic repeated newsvendor model--a f…
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
Fan Chen, Dylan J. Foster, Yanjun Han +3
We develop a unifying framework for information-theoretic lower bound in statistical estimation and interactive decision making. Classical lower bound techniques -- such as Fano's…
Statistical Properties of Robust Satisficing
Zhiyi Li, Yunbei Xu, Ruohan Zhan
The Robust Satisficing (RS) model is an emerging approach to robust optimization, offering streamlined procedures and robust generalization across various applications. However, th…