34 citations · 88 across the 16 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2022★ 1 cited
Estimating Gaussian Copulas with Missing Data
Maximilian Kertel, Markus Pauly
In this work we present a rigorous application of the Expectation Maximization algorithm to determine the marginal distributions and the dependence structure in a Gaussian copula m…
stat.ML2019
Asymptotic Unbiasedness of the Permutation Importance Measure in Random Forest Models
Burim Ramosaj, Markus Pauly
Variable selection in sparse regression models is an important task as applications ranging from biomedical research to econometrics have shown. Especially for higher dimensional r…
stat.ML2017★ 4 cited
Who wins the Miss Contest for Imputation Methods? Our Vote for Miss BooPF
Burim Ramosaj, Markus Pauly
Missing data is an expected issue when large amounts of data is collected, and several imputation techniques have been proposed to tackle this problem. Beneath classical approaches…