
Identifying important predictors in large data bases – multiple testing and model selection
This is a chapter of the forthcoming Handbook of Multiple Testing. We co...
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VARCLUST: clustering variables using dimensionality reduction
VARCLUST algorithm is proposed for clustering variables under the assump...
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A Power Analysis for Knockoffs with the Lasso CoefficientDifference Statistic
In a linear model with possibly many predictors, we consider variable se...
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The Strong Screening Rule for SLOPE
Extracting relevant features from data sets where the number of observat...
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Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control
In this paper, we propose a new estimation procedure for discovering the...
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Adaptive Bayesian SLOPE – Highdimensional Model Selection with Missing Values
The selection of variables with highdimensional and missing data is a m...
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On the asymptotic properties of SLOPE
Sorted LOne Penalized Estimator (SLOPE) is a relatively new convex opti...
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Fast and robust model selection based on ranks
We consider the problem of identifying important predictors in large dat...
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On the sign recovery given by the thresholded LASSO and thresholded Basis Pursuit
We consider the regression model, when the number of observations is sma...
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Highdimensional robust regression and outliers detection with SLOPE
The problems of outliers detection and robust regression in a highdimen...
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Fast SaddlePoint Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1Norm
In this paper we propose a primaldual proximal extragradient algorithm ...
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False Discoveries Occur Early on the Lasso Path
In regression settings where explanatory variables have very low correla...
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Malgorzata Bogdan
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