7 citations · 15 across the 5 of their papers we have counts for
5 papers
A solvable model for unsupervised federated learning
Giovanni Catania, Aurélien Decelle, Gianluca Manzan +2
We introduce a theoretical framework for analyzing federated learning in a generative setting through a teacher-multiple interacting students scenario, in which each student receiv…
Contagion Effects of Heterogeneous Cyber Risk on Network Security and Systemic Stability
Elisa Botteghi, Martino S. Centonze, Davide Pastorello +1
Understanding how heterogeneous cyber risk shapes security investments and contagion is a key challenge for the resilience of interconnected digital systems. Existing studies on cy…
Saddle Hierarchy in Dense Associative Memory
Robin Thériault, Daniele Tantari
Dense Associative Memory (DAM) models have been attracting renewed attention since they were shown to be robust to adversarial examples and closely related to cutting edge machine…
The effect of priors on Learning with Restricted Boltzmann Machines
Gianluca Manzan, Daniele Tantari
Restricted Boltzmann Machines (RBMs) are generative models designed to learn from data with a rich underlying structure. In this work, we explore a teacher-student setting where a…
Modeling Structured Data Learning with Restricted Boltzmann Machines in the Teacher-Student Setting
Robin Thériault, Francesco Tosello, Daniele Tantari
Restricted Boltzmann machines (RBM) are generative models capable to learn data with a rich underlying structure. We study the teacher-student setting where a student RBM learns st…