Statistics Seminar
Date/Time: | Monday, 13 Apr 2015 from 4:10 pm to 5:00 pm |
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Location: | Snedecor 3105 |
Cost: | Free |
URL: | www.stat.iastate.edu |
Contact: | Main Office |
Phone: | 515-294-3440 |
Channel: | College of Liberal Arts and Sciences |
Categories: | Lectures |
Actions: | Download iCal/vCal | Email Reminder |
Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Medical imaging and genomic studies generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. We propose a family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. Potential of the new method is demonstrated on simulated and real imaging data.