6 papers
Toward an Asymptotic Efficiency Theory on Regular Parameter Manifolds
Lvfang Sun, Zhenhua Lin, Lin Liu
Asymptotic efficiency theory is one of the pillars in the foundations of modern mathematical statistics. Not only does it serve as a rigorous theoretical benchmark for evaluating s…
Optimal estimation in private distributed functional data analysis
Gengyu Xue, Zhenhua Lin, Yi Yu
We systematically investigate the preservation of differential privacy in functional data analysis, beginning with functional mean estimation and extending to varying coefficient m…
Neural Wasserstein Two-Sample Tests
Xiaoyu Hu, Zhenhua Lin
The two-sample homogeneity testing problem is fundamental in statistics and becomes particularly challenging in high dimensions, where classical tests can suffer substantial power…
Multi-transport Distributional Regression
Yuanying Chen, Tongyu Li, Yang Bai +1
We study distribution-on-distribution regression problems in which a response distribution depends on multiple distributional predictors. Such settings arise naturally in applicati…
Fairness-aware Bayes optimal functional classification
Xiaoyu Hu, Gengyu Xue, Zhenhua Lin +1
Algorithmic fairness has become a central topic in machine learning, and mitigating disparities across different subpopulations has emerged as a rapidly growing research area. In t…
Transfer Learning Meets Functional Linear Regression: No Negative Transfer under Posterior Drift
Xiaoyu Hu, Zhenhua Lin
Posterior drift refers to changes in the relationship between responses and covariates while the distributions of the covariates remain unchanged. In this work, we explore function…