10 citations · 13 across the 7 of their papers we have counts for
7 papers
Deviation inequalities for U-processes of growing order, with applications to half-space depth
Stanislav Minsker, Shunan Yao
We prove new deviation inequalities for infinite-order U-processes, that is, U-processes whose order may increase with the sample size. Our goal is to obtain the sharpest possible…
Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
Jianqing Fan, Xin Tong, Yanhui Wu +2
Organizations often rely on statistical algorithms to make socially and economically impactful decisions. We must address the fairness issues in these important automated decisions…
Generalized Median of Means Principle for Bayesian Inference
Stanislav Minsker, Shunan Yao
The topic of robustness is experiencing a resurgence of interest in the statistical and machine learning communities. In particular, robust algorithms making use of the so-called m…
Asymmetric error control under imperfect supervision: a label-noise-adjusted Neyman-Pearson umbrella algorithm
Shunan Yao, Bradley Rava, Xin Tong +1
Label noise in data has long been an important problem in supervised learning applications as it affects the effectiveness of many widely used classification methods. Recently, imp…
Distance-based and RKHS-based Dependence Metrics in High Dimension
Changbo Zhu, Shun Yao, Xianyang Zhang +1
In this paper, we study distance covariance, Hilbert-Schmidt covariance (aka Hilbert-Schmidt independence criterion [Gretton et al. (2008)]) and related independence tests under th…
Conditional Mean and Quantile Dependence Testing in High Dimension
Xianyang Zhang, Shun Yao, Xiaofeng Shao
Motivated by applications in biological science, we propose a novel test to assess the conditional mean dependence of a response variable on a large number of covariates. Our proce…
Testing mutual independence in high dimension via distance covariance
Shun Yao, Xianyang Zhang, Xiaofeng Shao
In this paper, we introduce a type test for testing mutual independence and banded dependence structure for high dimensional data. The test is constructed based on…