3 papers
math.ST2026
Semiparametric semi-supervised learning for general targets under distribution shift and decaying overlap
Lorenzo Testa, Qi Xu, Jing Lei +1
In modern scientific applications, large volumes of covariate data are readily available, while outcome labels are costly, sparse, and often subject to distribution shift. This asy…
stat.ME2026
Sparse group principal component analysis via double thresholding with application to multi-cellular programs
Qi Xu, Jing Lei, Kathryn Roeder
Multi-cellular programs (MCPs) are coordinated patterns of gene expression across interacting cell types that collectively drive complex biological processes such as tissue develop…
stat.ME2025
Towards Efficient Inference under Nonmonotone Missingness with General Imputation
Qi Xu, Lorenzo Testa, Jing Lei +1
Missing data are ubiquitous in classical survey and longitudinal studies as well as modern multi-modality data analysis. A longstanding challenge arises under nonmonotone missingne…