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• W2783455002 abstract "Let $Y$ be a $d$-dimensional random vector with unknown mean $mu$ and covariance matrix $Sigma$. This paper is motivated by the problem of designing an estimator of $Sigma$ that admits tight deviation bounds in the operator norm under minimal assumptions on the underlying distribution, such as existence of only 4th moments of the coordinates of $Y$. To address this problem, we propose robust modifications of the operator-valued U-statistics, obtain non-asymptotic guarantees for their performance, and demonstrate the implications of these results to the covariance estimation problem under various structural assumptions." @default.
• W2783455002 created "2018-01-26" @default.
• W2783455002 creator A5035506999 @default.
• W2783455002 creator A5059637342 @default.
• W2783455002 date "2018-01-17" @default.
• W2783455002 modified "2023-10-11" @default.
• W2783455002 title "Robust Modifications of U-statistics and Applications to Covariance Estimation Problems" @default.
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• W2783455002 doi "https://doi.org/10.48550/arxiv.1801.05565" @default.
• W2783455002 hasPublicationYear "2018" @default.
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