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Dimension-free PAC-Bayesian bounds for the estimation of the mean of a random vector

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arxiv 1802.04308 v1 pith:BUAXNMOY submitted 2018-02-12 math.ST stat.TH

Dimension-free PAC-Bayesian bounds for the estimation of the mean of a random vector

Olivier Catoni , Ilaria Giulini This is my paper
classification math.ST stat.TH
keywords boundsdimension-freemeanpac-bayesianrandomvectoralmostapplying
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this paper, we present a new estimator of the mean of a random vector, computed by applying some threshold function to the norm. Non asymptotic dimension-free almost sub-Gaussian bounds are proved under weak moment assumptions, using PAC-Bayesian inequalities.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. HOMER: Huber-of-Means for Efficient and Robust Estimation in Hilbert Spaces

    stat.ML 2026-07 conditional novelty 6.0

    HOMER replaces the geometric median in median-of-means with a radial Huber center, giving heavy-tail robustness and threshold-controlled mean inference in Hilbert spaces.