2 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
Low-degree phase transitions for detecting a planted clique in sublinear time
Jay Mardia, Kabir Aladin Verchand, Alexander S. Wein
We consider the problem of detecting a planted clique of size in a random graph on vertices. When the size of the clique exceeds , polynomial-time algorithms f…
Hyperparameter tuning via trajectory predictions: Stochastic prox-linear methods in matrix sensing
Mengqi Lou, Kabir Aladin Verchand, Ashwin Pananjady
Motivated by the desire to understand stochastic algorithms for nonconvex optimization that are robust to their hyperparameter choices, we analyze a mini-batched prox-linear iterat…