3 papers
cs.LG2026
When pre-training hurts LoRA fine-tuning: a dynamical analysis via single-index models
Gibbs Nwemadji, Bruno Loureiro, Jean Barbier
Pre-training on a source task is usually expected to facilitate fine-tuning on similar downstream problems. In this work, we mathematically show that this naive intuition is not al…
cond-mat.dis-nn2025
Generalization performance of narrow one-hidden layer networks in the teacher-student setting
Rodrigo Pérez Ortiz, Gibbs Nwemadji, Jean Barbier +4
Understanding the generalization properties of neural networks on simple input-output distributions is key to explaining their performance on real datasets. The classical teacher-s…
quant-ph2023
On the capacity of a quantum perceptron for storing biased patterns
Fabio Benatti, Giovanni Gramegna, Stefano Mancini +1
Although different architectures of quantum perceptrons have been recently put forward, the capabilities of such quantum devices versus their classical counterparts remain debated.…