@inproceedings{f3eeead577ce448da0b0e6e971f85a32,
title = "Automatic diagonal loading for Tyler's robust covariance estimator",
abstract = "An approach of regularizing Tyler's robust M-estimator of the co-variance matrix is proposed. We also provide an automatic choice of the regularization parameter in the high-dimensional regime. Simulations show its advantage over the sample covariance estimator and Tyler's M-estimator when data is heavy-tailed and the number of samples is small. Compared with the previous approaches of regularizing Tyler's M-estimator, our approach has a similar performance and a much simpler way of choosing the regularization parameter automatically.",
keywords = "Robust estimation, high-dimensional statistics",
author = "Teng Zhang and Ami Wiesel",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 19th IEEE Statistical Signal Processing Workshop, SSP 2016 ; Conference date: 25-06-2016 Through 29-06-2016",
year = "2016",
month = aug,
day = "24",
doi = "10.1109/SSP.2016.7551741",
language = "الإنجليزيّة",
series = "IEEE Workshop on Statistical Signal Processing Proceedings",
publisher = "IEEE Computer Society",
booktitle = "2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016",
address = "الولايات المتّحدة",
}