Search Results for author: Tino Werner

Found 5 papers, 0 papers with code

Global quantitative robustness of regression feed-forward neural networks

no code implementations18 Nov 2022 Tino Werner

Neural networks are an indispensable model class for many complex learning tasks.

regression

Loss-guided Stability Selection

no code implementations10 Feb 2022 Tino Werner

Since model selection depends on the loss function, i. e., predictor sets selected w. r. t.

Binary Classification Model Selection

The column measure and Gradient-Free Gradient Boosting

no code implementations24 Sep 2019 Tino Werner, Peter Ruckdeschel

The fact that certain variables relevant for a particular loss $\tilde L$ never get selected by $L_2-$Boosting is reflected by a respective singular part of $\nu^{(\tilde L)}$ w. r. t.

Computational Efficiency Model Selection +1

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