The Penn State University
(A reception will precede the event at 4:00 pm in 101A Crowley Hall)
Feature screening for ultrahigh dimensional data: Methods and Applications
Analysis of ultrahigh-dimensional data plays critical roles in big data analysis. Feature screening aims to quickly reduce the dimensionality by filtering out irrelevant variables as many as possible without excluding out important variables. Thus, feature screening is an important statistical analytic tool for ultrahigh data. There have been many developments on this topic. In this lecture, I will present general strategy and some applications of feature screening.