Xiangrong Yin
Department of Statistics
University of Georgia
Solution Paths for Large p Small n Problems
In this talk, I will introduce a new but very simple framework
to solve the large p small n problems. The framework decomposes the data
into pieces so that existing methods can be applied. We propose two separate
paths to implement the framework. Our paths provide sufficient procedures for
identifying informative variables sequentially. The paths are very general
and we shall illustrate their efficacy via simulation and a real data set by
using sufficient dimension reduction and variable selection methods.
(Joint work with Haileab Hilafu)
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