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AMS Special Seminar Series | Alden Green
February 20 @ 10:00 am - 11:00 am
Location: Clark 110
When: February 20th at 10:00 a.m.
Title: The High-Dimensional Asymptotics of Principal Components Regression
Abstract: We study principal components regression (PCR) in an asymptotic high-dimensional setting, where the number of data points is proportional to the dimension. We derive exact limiting formulas for estimation and prediction risk, which depend in a complicated manner on the eigenvalues of the population covariance, the alignment between the population PCs and the true signal, and the number of selected PCs. A key challenge in the high-dimensional setting stems from the fact that the sample covariance is an inconsistent estimate of its population counterpart, so that sample PCs may fail to fully capture potential latent low-dimensional structure in the data. We demonstrate this point through several case studies, including that of a spiked covariance model.
Zoom link: https://wse.zoom.us/j/92755277282?pwd=iULpLaFnWAcWl6tQYUbeyZaN3zwBzn.1