Boltzmann machines with clusters of stochastic binary units
Da Teng, Zhang Li, Guanghong Gong, Liang Han · Advances in Complex Systems · 2016
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.