4 citations · 6 across the 4 of their papers we have counts for
5 papers
An Approach of Bayesian Variable Selection for Ultrahigh Dimensional Multivariate Regression
Xiaotian Dai, Guifang Fu, Randall Reese +2
In many practices, scientists are particularly interested in detecting which of the predictors are truly associated with a multivariate response. It is more accurate to model multi…
Epistasis Detection Via the Joint Cumulant
Randall Reese, Guifang Fu, Geran Zhao +3
Selecting influential nonlinear interactive features from ultrahigh dimensional data has been an important task in various fields. However, statistical accuracy and computational f…
Marginal and Interactive Feature Screening of Ultra-high Dimensional Feature Spaces with Multivariate Response
Randall Reese
When the number of features exponentially outnumbers the number of samples, feature screening plays a pivotal role in reducing the dimension of the feature space and developing mod…
Strong Sure Screening of Ultra-high Dimensional Categorical Data
Randall Reese, Xiaotian Dai, Guifang Fu
Feature screening for ultra high dimensional feature spaces plays a critical role in the analysis of data sets whose predictors exponentially exceed the number of observations. Suc…
Strong Sure Screening of Ultra-high Dimensional Data with Interaction Effects
Randall Reese, Xiaotian Dai, Guifang Fu
Ultrahigh dimensional data sets are becoming increasingly prevalent in areas such as bioinformatics, medical imaging, and social network analysis. Sure independent screening of suc…