17 citations · 32 across the 14 of their papers we have counts for
3 papers · 1 filter
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures
Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia +4
This paper considers the Pointer Value Retrieval (PVR) benchmark introduced in [ZRKB21], where a 'reasoning' function acts on a string of digits to produce the label. More generall…
Learning curves for the multi-class teacher-student perceptron
Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga +3
One of the most classical results in high-dimensional learning theory provides a closed-form expression for the generalisation error of binary classification with the single-layer…
An initial alignment between neural network and target is needed for gradient descent to learn
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła +1
This paper introduces the notion of ``Initial Alignment'' (INAL) between a neural network at initialization and a target function. It is proved that if a network and a Boolean targ…