2 papers
cs.LG2025
Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data
David Holzmüller, Léo Grinsztajn, Ingo Steinwart
For classification and regression on tabular data, the dominance of gradient-boosted decision trees (GBDTs) has recently been challenged by often much slower deep learning methods…
stat.ML2024
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
Moritz Haas, David Holzmüller, Ulrike von Luxburg +1
The success of over-parameterized neural networks trained to near-zero training error has caused great interest in the phenomenon of benign overfitting, where estimators are statis…