Pattern recognition in Deep Boltzmann machines
Disordered Systems and Neural Networks
2022-02-21 v1 Mathematical Physics
math.MP
Abstract
We consider a multi-layer Sherrington-Kirkpatrick spin-glass as a model for deep restricted Boltzmann machines and we solve for its quenched free energy, in the thermodynamic limit and allowing for a first step of replica symmetry breaking. This result is accomplished rigorously exploiting interpolating techniques and recovering the expression already known for the replica-symmetry case. Further, we drop the restriction constraint by introducing intra-layer connections among spins and we show that the resulting system can be mapped into a modular Hopfield network, which is also addressed rigorously via interpolating techniques up to the first step of replica symmetry breaking.
Keywords
Cite
@article{arxiv.2106.08978,
title = {Pattern recognition in Deep Boltzmann machines},
author = {Elena Agliari and Linda Albanese and Francesco Alemanno and Alberto Fachechi},
journal= {arXiv preprint arXiv:2106.08978},
year = {2022}
}
Comments
24 pages, 2 figures