2 citations · 3 across the 8 of their papers we have counts for
3 papers · 2 filters
Estimation beyond Missing (Completely) at Random
Tianyi Ma, Kabir A. Verchand, Thomas B. Berrett +2
We study the effects of missingness on the estimation of population parameters. Moving beyond restrictive missing completely at random (MCAR) assumptions, we first formulate a miss…
High-dimensional logistic regression with missing data: Imputation, regularization, and universality
Kabir Aladin Verchand, Andrea Montanari
We study high-dimensional, ridge-regularized logistic regression in a setting in which the covariates may be missing or corrupted by additive noise. When both the covariates and th…
High-probability minimax lower bounds
Tianyi Ma, Kabir A. Verchand, Richard J. Samworth
The minimax risk is often considered as a gold standard against which we can compare specific statistical procedures. Nevertheless, as has been observed recently in robust and heav…