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math.ST2021
Quantitative robustness of instance ranking problems
Tino Werner
Instance ranking problems intend to recover the true ordering of the instances in a data set with a variety of applications in for example scientific, social and financial contexts…
math.ST2019★ 2 cited
The column measure and Gradient-Free Gradient Boosting
Tino Werner, Peter Ruckdeschel
Sparse model selection by structural risk minimization leads to a set of a few predictors, ideally a subset of the true predictors. This selection clearly depends on the underlying…
math.ST2019
Asymptotic linear expansion of regularized M-estimators
Tino Werner
Parametric high-dimensional regression analysis requires the usage of regularization terms to get interpretable models. The respective estimators can be regarded as regularized M-f…