##Statistics Seminar##\\ Department of Mathematical Sciences
^ **DATE:**|Thursday, September 23, 2021 |
^ **TIME:**|1:15pm -- 2:15pm |
^ **LOCATION:**|Zoom meeting |
^ **SPEAKER:**|Shaofei Zhao, Binghamton University |
^ **TITLE:**|Feature selection on tensor response data |
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**Abstract**
We have seen several feature selection approaches for ultrahigh
dimensional data recently. However, most of the approaches are applicable
for n*1, or at most n*q response variables. If we encounter a more complex
data structure when the response is tensor-shaped, e.g. human facial shape,
multi-omics gene data, Electroencephalography (EEG), or functional
magnetic resonance imaging (fMRI), current feature selection approaches
will have difficulty to handle the data. We propose a simple yet useful
feature selection method that can be applied to tensor response data, and
show the selection consistency of our method.