3 papers
stat.ME2026
Distributed Convoluted Rank Regression for Non-Shareable Data under Non-Additive Losses
Wen Zhang, Liping Zhu, Songshan Yang
We study high-dimensional rank regression when data are distributed across multiple machines and the loss is a non-additive U-statistic, as in convoluted rank regression (CRR). Cla…
stat.ME2025
Do more observations bring more information in rare events?
Danyang Huang, Liyuan Wang, Liping Zhu
It is generally believed that more observations provide more information. However, we observe that in the independence test for rare events, the power of the test is, surprisingly,…
stat.ME2024
Reducing multivariate independence testing to two bivariate means comparisons
Kai Xu, Yeqing Zhou, Liping Zhu +1
Testing for independence between two random vectors is a fundamental problem in statistics. It is observed from empirical studies that many existing omnibus consistent tests may no…