15 citations · 16 across the 8 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2023
Strong inductive biases provably prevent harmless interpolation
Michael Aerni, Marco Milanta, Konstantin Donhauser +1
Classical wisdom suggests that estimators should avoid fitting noise to achieve good generalization. In contrast, modern overparameterized models can yield small test error despite…
stat.ML2021★ 1 cited
Interpolation can hurt robust generalization even when there is no noise
Konstantin Donhauser, Alexandru Ţifrea, Michael Aerni +2
Numerous recent works show that overparameterization implicitly reduces variance for min-norm interpolators and max-margin classifiers. These findings suggest that ridge regulariza…