2 papers
cs.LG2025
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Chris Kolb, Tobias Weber, Bernd Bischl +1
Sparse regularization techniques are well-established in machine learning, yet their application in neural networks remains challenging due to the non-differentiability of penaltie…
cs.LG2024
Generalizing Orthogonalization for Models with Non-Linearities
David Rügamer, Chris Kolb, Tobias Weber +2
The complexity of black-box algorithms can lead to various challenges, including the introduction of biases. These biases present immediate risks in the algorithms' application. It…