1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Achieving Data Efficient Neural Networks with Hybrid Concept-based Models
Tobias A. Opsahl, Vegard Antun
Most datasets used for supervised machine learning consist of a single label per data point. However, in cases where more information than just the class label is available, would…
cs.LG2023★ 1 cited
Implicit regularization in AI meets generalized hardness of approximation in optimization -- Sharp results for diagonal linear networks
Johan S. Wind, Vegard Antun, Anders C. Hansen
Understanding the implicit regularization imposed by neural network architectures and gradient based optimization methods is a key challenge in deep learning and AI. In this work w…