2 papers
cond-mat.dis-nn2022
Universal mean field upper bound for the generalisation gap of deep neural networks
S. Ariosto, R. Pacelli, F. Ginelli +2
Modern deep neural networks (DNNs) represent a formidable challenge for theorists: according to the commonly accepted probabilistic framework that describes their performance, thes…
cond-mat.stat-mech2020
Random geometric graphs in high dimension
Vittorio Erba, Sebastiano Ariosto, Marco Gherardi +1
Many machine learning algorithms used for dimensional reduction and manifold learning leverage on the computation of the nearest neighbours to each point of a dataset to perform th…