arXiv Machine Learning
Oct 16

Attention over noisy examples: generalization and memorization in the exponential Hopfield network

arXiv:2610. 22191v1 Announce Type: cross Abstract: In Hebbian learning from examples a Hopfield network of $N$ neurons is not supplied with the $K$ archetypes it has to retrieve but with $M$ blurred examples of each, of quality $r$, and whether it can infer them depends on the load $\alpha=K/N$ (interference among them) and on the dataset entropy $\rho=(1-r^2)/(Mr^2)$ (how little the examples say about them).

By Francesco Alemanno