Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Verchand, Kabir A."'
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 missing data analogue of Huber's arbitrary $\epsilon$-contamination model.
Externí odkaz:
http://arxiv.org/abs/2410.10704
High-dimensional logistic regression with missing data: Imputation, regularization, and universality
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 the additive corruptions are independent and normally distributed, we pr
Externí odkaz:
http://arxiv.org/abs/2410.01093
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 heavy-tailed estimation problems, the inherent reduction of the (random) l
Externí odkaz:
http://arxiv.org/abs/2406.13447
We consider the problem of detecting a planted clique of size $k$ in a random graph on $n$ vertices. When the size of the clique exceeds $\Theta(\sqrt{n})$, polynomial-time algorithms for detection proliferate. We study faster -- namely, sublinear ti
Externí odkaz:
http://arxiv.org/abs/2402.05451
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 iterative algorithm for the problem of recovering an unknown rank-1 matrix f
Externí odkaz:
http://arxiv.org/abs/2402.01599