Konstantin Donhauser

According to our database, Konstantin Donhauser authored at least 20 papers between 2019 and 2025.

Collaborative distances:

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

2025

Unveiling Simplicities of Attention: Adaptive Long-Context Head Identification.

Konstantin Donhauser, Charles Arnal, Mohammad Pezeshki, Vivien Cabannes, David Lopez-Paz, Kartik Ahuja

CoRR, February, 2025

Efficient Randomized Experiments Using Foundation Models.

Piersilvio De Bartolomeis, Javier Abad, Guanbo Wang, Konstantin Donhauser, Raymond M. Duch, Fanny Yang, Issa J. Dahabreh

CoRR, February, 2025

Copyright-Protected Language Generation via Adaptive Model Fusion.

Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models.

Konstantin Donhauser, Kristina Ulicna, Gemma E. Moran, Aditya Ravuri, Kian Kenyon-Dean, Cian Eastwood, Jason S. Hartford

CoRR, 2024

ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy.

Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik, Konstantin Donhauser, Jason S. Hartford, Saber Saberian, Nil Sahin, Ihab Bendidi, Safiye Celik, Marta M. Fay, Juan Sebastian Rodriguez Vera, Imran S. Haque, Oren Kraus

CoRR, 2024

Strong Copyright Protection for Language Models via Adaptive Model Fusion.

Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang

CoRR, 2024

Detecting critical treatment effect bias in small subgroups.

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

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent.

Konstantin Donhauser, Javier Abad Martinez, Neha Hulkund, Fanny Yang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tight bounds for maximum ℓ₁-margin classifiers.

Stefan Stojanovic, Konstantin Donhauser, Fanny Yang

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

Certified private data release for sparse Lipschitz functions.

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

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

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

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

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