Paper: Learning a Spin Glass

[Renato Vicente]

Dear Connectionists,


We would like to announce our new paper on statistical physics of 
neural networks. The paper is available at:

http://www.fma.if.usp.br/~rvicente/nnsp.html/NNGUSP13.ps.gz

Comments are welcome.

 


Learning a spin glass: determining Hamiltonians from metastable states.
------------------------------------------------------------------------
SILVIA KUVA, OSAME KINOUCHI and NESTOR CATICHA


Abstract:

We study the problem of determining the Hamiltonian of a fully connected
Ising Spin Glass of $N$ units from a set of measurements, whose sizes needs
to be ${\cal O}(N^2)$ bits. The student-teacher scenario, used to study learning
in feed-forward neural networks, is here extended to 
spin systems with arbitrary couplings.
The set of measurements consists of data about the local
minima of the rugged energy landscape.
We compare simulations and analytical approximations for the resulting 
learning curves obtained by using different algorithms.