Tootfinder

Generalization performance of narrow one-hidden layer networks in the teacher-student setting
Jean Barbier, Federica Gerace, Alessandro Ingrosso, Clarissa Lauditi, Enrico M. Malatesta, Gibbs Nwemadji, Rodrigo P\'erez Ortiz
https://arxiv.org/abs/2507.00629

Generalization performance of narrow one-hidden layer networks in the teacher-student setting
Understanding the generalization abilities of neural networks for simple input-output distributions is crucial to account for their learning performance on real datasets. The classical teacher-student setting, where a network is trained from data obtained thanks to a label-generating teacher model, serves as a perfect theoretical test bed. In this context, a complete theoretical account of the performance of fully connected one-hidden layer networks in the presence of generic activation functio…

Replaced article(s) found for cond-mat.dis-nn. https://arxiv.org/list/cond-mat.dis-nn/new
[1/1]:
- Sampling the space of solutions of an artificial neural network
Alessandro Zambon, Enrico M. Malatesta, Guido Tiana, Riccardo Zecchina