Konstantin Donhauser

According to our database, Konstantin Donhauser authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Privacy-preserving data release leveraging optimal transport and particle gradient descent.

Konstantin Donhauser, Javier Abad, Neha Hulkund, Fanny Yang

CoRR, 2024

2023

Hidden yet quantifiable: A lower bound for confounding strength using randomized trials.

Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang

CoRR, 2023

Sample-efficient private data release for Lipschitz functions under sparsity assumptions.

Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang

CoRR, 2023

Strong inductive biases provably prevent harmless interpolation.

Michael Aerni, Marco Milanta, Konstantin Donhauser, Fanny Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Tight bounds for maximum 𝓁₁-margin classifiers.

Stefan Stojanovic, Konstantin Donhauser, Fanny Yang

CoRR, 2022

Fast rates for noisy interpolation require rethinking the effects of inductive bias.

Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang

CoRR, 2022

Fast rates for noisy interpolation require rethinking the effect of inductive bias.

Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang

Proceedings of the International Conference on Machine Learning, 2022

Tight bounds for minimum ℓ₁-norm interpolation of noisy data.

Guillaume Wang, Konstantin Donhauser, Fanny Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Tight bounds for minimum l1-norm interpolation of noisy data.

Guillaume Wang, Konstantin Donhauser, Fanny Yang

CoRR, 2021

Interpolation can hurt robust generalization even when there is no noise.

Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How rotational invariance of common kernels prevents generalization in high dimensions.

Konstantin Donhauser, Mingqi Wu, Fanny Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Efficient Smoothing of Dilated Convolutions for Image Segmentation.

Thomas Ziegler, Manuel Fritsche, Lorenz Kuhn, Konstantin Donhauser

CoRR, 2019