% Version 1.000
%
% Code provided by Geo Hinton and Ruslan Salakhutdinov
%
% Permission is granted for anyone to copy, use, modify, or
distribute this
% program and accompanying programs and documents for any
purpose, provided
% this copyright notice is retained and prominently displayed, along
with
% a note saying that the original programs are available from our
% web page.
% The programs and documents are distributed without any
warranty, express or
% implied. As the programs were written for research purposes
only, they have
% not been tested to the degree that would be advisable in any
important
% application. All use of these programs is entirely at the user's
own risk.
% This program trains Restricted Boltzmann Machine in which
% visible, binary, stochastic pixels are connected to
% hidden, binary, stochastic feature detectors using symmetrically
% weighted connections. Learning is done with 1-step Contrastive
Divergence.
% The program assumes that the following variables are set
externally:
% maxepoch -- maximum number of epochs
% numhid -- number of hidden units
% batchdata -- the data that is divided into batches (numcases
numdims numbatches)
% restart -- set to 1 if learning starts from beginning
epsilonw = 0.1; % Learning rate for weights
epsilonvb = 0.1; % Learning rate for biases of visible units
epsilonhb = 0.1; % Learning rate for biases of hidden units
weightcost = 0.0002;