A spectral least-squares-type method for heavy-tailed corrupted regression with unknown covariance \& heterogeneous noise

Roberto I. Oliveira, Zoraida F. Rico, Philip Thompson

We revisit heavy-tailed corrupted least-squares linear regression assuming to have a corrupted $n$-sized label-feature sample of at most $\epsilon n$ arbitrary outliers. We wish to estimat…