2017
Estimation of the covariance structure of heavy-tailed distributions
NeurIPS 2017poster
We propose and analyze a new estimator of the covariance matrix that admits strong theoretical guarantees under weak assumptions on the underlying distribution, such as existence of moments of only low order. While estimation of covariance matrices corresponding to sub-Gaussian distributions is well…