Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing

We develop two methods for the following fundamental statistical task: given an ɛ-corrupted set of n samples from a d-dimensional sub-Gaussian distribution, return an approximate top eigenvector of the covariance matrix.