8 papers
Tuning-Free Efficient Estimation for Multi-Source Data via Covariance-Aware Shrinkage
Wenbo Jing, Xi Chen, Yaqi Duan +2
Modern statistical learning problems often involve multiple related data sets, where learning efficiency on a target set can be improved by utilizing related source sets, while het…
Binomial Smoothing for Inventory and Information Control in Supply Chains
Rene Caldentey, Avi Giloni, Clifford Hurvich +2
In many decentralized supply chains, upstream firms do not observe market demand directly and instead infer downstream conditions from the order stream. A retailer's replenishment…
Generalized Rank Regression
Jiyuan Tu, Suqi Wu, Yichen Zhang +1
Rank regression offers robustness to outliers and heavy-tailed response distributions, invariance to monotonic transformations, and improved efficiency under non-Gaussian errors, m…
Policy-Aware Design of Large-Scale Factorial Experiments
Xin Wen, Xi Chen, Will Wei Sun +1
Digital firms routinely run many online experiments on shared user populations. When product decisions are compositional, such as combinations of interface elements, flows, message…
Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent
Xiangyu Chang, Xi Chen, Zehua Lai +3
With the fast development of big data, learning the optimal decision rule by recursively updating it and making online decisions has been easier than before. We study the online st…
Online Statistical Inference in Decision-Making with Matrix Context
Qiyu Han, Will Wei Sun, Yichen Zhang
The study of online decision-making problems that leverage contextual information has drawn notable attention due to their significant applications in fields ranging from healthcar…