291 citations · 936 across the 29 of their papers we have counts for
9 papers · 1 filter
Sparse Graphical Modelling via the Sorted L-Norm
Riccardo Riccobello, Malgorzata Bogdan, Giovanni Bonaccolto +3
Sparse graphical modelling has attained widespread attention across various academic fields. We propose two new graphical model approaches, Gslope and Tslope, which provide sparse…
Identifying important predictors in large data bases -- multiple testing and model selection
Malgorzata Bogdan, Florian Frommlet
This is a chapter of the forthcoming Handbook of Multiple Testing. We consider a variety of model selection strategies in a high-dimensional setting, where the number of potential…
Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values
Wei Jiang, Malgorzata Bogdan, Julie Josse +3
We consider the problem of variable selection in high-dimensional settings with missing observations among the covariates. To address this relatively understudied problem, we propo…
Nonparametric Shrinkage Estimation in High Dimensional Generalized Linear Models via Polya Trees
Asaf Weinstein, Jonas Wallin, Daniel Yekutieli +1
Regularization in fitting regression models has been a highly active topic of research in the past few decades, but most of the existing methods are designed for particular situati…
Rank-based Lasso -- efficient methods for high-dimensional robust model selection
Wojciech Rejchel, Malgorzata Bogdan
We consider the problem of identifying significant predictors in large data bases, where the response variable depends on the linear combination of explanatory variables through an…
On the sign recovery by LASSO, thresholded LASSO and thresholded Basis Pursuit Denoising
Patrick J. C. Tardivel, Malgorzata Bogdan
Basis Pursuit (BP), Basis Pursuit DeNoising (BPDN), and LASSO are popular methods for identifying important predictors in the high-dimensional linear regression model, i.e. when th…