3 papers
math.PR2021
Shrinkage Estimation of Functions of Large Noisy Symmetric Matrices
Panagiotis Lolas, Lexing Ying
We study the problem of estimating functions of a large symmetric matrix when we only have access to a noisy estimate We are interested in the…
stat.ME2020
-Ridge: group regularized ridge regression via empirical Bayes noise level cross-validation
Nikolaos Ignatiadis, Panagiotis Lolas
Features in predictive models are not exchangeable, yet common supervised models treat them as such. Here we study ridge regression when the analyst can partition the features into…
math.ST2020
Regularization in High-Dimensional Regression and Classification via Random Matrix Theory
Panagiotis Lolas
We study general singular value shrinkage estimators in high-dimensional regression and classification, when the number of features and the sample size both grow proportionally to…