4 papers
Tuning-Free Covariance-Aware Sequential Shrinkage for Multi-Source Estimation
Wenbo Jing, Xi Chen, Yaqi Duan +2
Modern statistical learning problems often involve multiple related data sets, in which learning efficiency on a target set can be improved by borrowing information from related so…
High-Dimensional Linear Bandits under Stochastic Latent Heterogeneity
Elynn Chen, Xi Chen, Wenbo Jing +1
This paper addresses the critical challenge of stochastic latent heterogeneity in online decision-making, where individuals' responses to actions vary not only with observable cont…
Distributed Tensor Principal Component Analysis with Data Heterogeneity
Elynn Chen, Xi Chen, Wenbo Jing +1
As tensors become widespread in modern data analysis, Tucker low-rank Principal Component Analysis (PCA) has become essential for dimensionality reduction and structural discovery…
Data-Driven Knowledge Transfer in Batch Learning
Elynn Chen, Xi Chen, Wenbo Jing
In data-driven decision-making in marketing, healthcare, and education, it is desirable to utilize a large amount of data from existing ventures to navigate high-dimensional featur…