31 citations · 35 across the 3 of their papers we have counts for
7 papers
Model-based Sparse Coding beyond Gaussian Independent Model
Xin Xing, Rui Xie, Wenxuan Zhong
Sparse coding aims to model data vectors as sparse linear combinations of basis elements, but a majority of related studies are restricted to continuous data without spatial or tem…
Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks
Xin Xing, Yu Gui, Chenguang Dai +1
Deep neural networks (DNNs) have become increasingly popular and achieved outstanding performance in predictive tasks. However, the DNN framework itself cannot inform the user whic…
A Scale-free Approach for False Discovery Rate Control in Generalized Linear Models
Chenguang Dai, Buyu Lin, Xin Xing +1
The generalized linear models (GLM) have been widely used in practice to model non-Gaussian response variables. When the number of explanatory features is relatively large, scienti…
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing +2
The statistical analysis of Randomized Numerical Linear Algebra (RandNLA) algorithms within the past few years has mostly focused on their performance as point estimators. However,…
False Discovery Rate Control via Data Splitting
Chenguang Dai, Buyu Lin, Xin Xing +1
Selecting relevant features associated with a given response variable is an important issue in many scientific fields. Quantifying quality and uncertainty of a selection result via…
Controlling False Discovery Rate Using Gaussian Mirrors
Xin Xing, Zhigen Zhao, Jun S. Liu
Simultaneously finding multiple influential variables and controlling the false discovery rate (FDR) for linear regression models is a fundamental problem. We here propose the Gaus…