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math.ST2025
On identification in ill-posed linear regression
Gianluca Finocchio, Tatyana Krivobokova
A novel framework is introduced to formalize identifiability in well-specified but ill-posed linear regression models. The framework is distribution-free and accommodates highly co…
math.ST2021
Robust-to-outliers square-root LASSO, simultaneous inference with a MOM approach
G. Finocchio, A. Derumigny, K. Proksch
We consider the least-squares regression problem with unknown noise variance, where the observed data points are allowed to be corrupted by outliers. Building on the median-of-mean…
math.ST2019
Bayesian variance estimation in the Gaussian sequence model with partial information on the means
Gianluca Finocchio, Johannes Schmidt-Hieber
Consider the Gaussian sequence model under the additional assumption that a fixed fraction of the means is known. We study the problem of variance estimation from a frequentist Bay…