activity
20222026
most citedImproved covariance estimation: optimal robustness and sub-Gaussian guarantees under heavy tails

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

math.ST2026

Robust dimension-free estimation of simple random tensors: optimal guarantees under heavy tails and adversarial contamination

Roberto I. Oliveira, Zoraida F. Rico, Philip Thompson

We study robust estimation of simple random tensors of arbitrary order under finite-moment assumptions and adversarial contamination. We propose the first robust e…

math.ST2025

Robust, sub-Gaussian mean estimators in metric spaces

Daniel Bartl, Gabor Lugosi, Roberto Imbuzeiro Oliveira +1

Estimating the mean of a random vector from i.i.d. data has received considerable attention, and the optimal accuracy one may achieve with a given confidence is fairly well underst…

math.ST2025

Finite-sample properties of the trimmed mean

Roberto I. Oliveira, Paulo Orenstein, Zoraida F. Rico

The trimmed mean of scalar random variables from a distribution is the variant of the standard sample mean where the smallest and largest values in the sample are d…

math.ST2022

A spectral least-squares-type method for heavy-tailed corrupted regression with unknown covariance \& heterogeneous noise

Roberto I. Oliveira, Zoraida F. Rico, Philip Thompson

We revisit heavy-tailed corrupted least-squares linear regression assuming to have a corrupted -sized label-feature sample of at most arbitrary outliers. We wish to estimat…

math.ST2022★ 2 cited

Improved covariance estimation: optimal robustness and sub-Gaussian guarantees under heavy tails

Roberto I. Oliveira, Zoraida F. Rico

We present an estimator of the covariance matrix of random -dimensional vector from an i.i.d. sample of size . Our sole assumption is that this vector satisfies a bounded…