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We propose an estimator for the mean of a random vector in $\mathbb{R}^d$ that can be computed in time $O(n^4+n^2d)$ for $n$ i.i.d.~samples and that has error bounds matching the sub-Gaussian case.
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Sub-Gaussian mean estimators
L. Devroye, M. Lerasle, G. Lugosi, and R. I. Oliveira · 2016
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S. B Hopkins · 2018
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Sub-Gaussian estimators of the mean of a random vector
G. Lugosi and S. Mendelson · 2019
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