Boltzmann machines with clusters of stochastic binary units
2016 ◽
Vol 07
(02)
◽
pp. 1650018
Keyword(s):
The original restricted Boltzmann machines (RBMs) are extended by replacing the binary visible and hidden variables with clusters of binary units, and a new learning algorithm for training deep Boltzmann machine of this new variant is proposed. The sum of binary units of each cluster is approximated by a Gaussian distribution. Experiments demonstrate that the proposed Boltzmann machines can achieve good performance in the MNIST handwritten digital recognition task.
2018 ◽
Vol 18
(1&2)
◽
pp. 51-74
◽
2021 ◽
2011 ◽
Vol 2
(2)
◽
pp. 153-164
◽
2015 ◽
Vol 2015
◽
pp. 1-9
◽