An Overview of Restricted Boltzmann Machines

Abstract

The restricted Boltzmann machine (RBM) is a two-layered network
of stochastic units with undirected connections between pairs of
units in the two layers. The two layers of nodes are called visible and hidden
nodes. In an RBM, there are no connections from visible to visible or
hidden to hidden nodes. RBMs are used mainly as a generative model.
They can be suitably modified to perform classification tasks also. They
are among the basic building blocks of other deep learning models
such as deep Boltzmann machine and deep belief networks. The aim
of this article is to give a tutorial introduction to the restricted Boltzmann
machines and to review the evolution of this model.