Data Processing Using Restricted Boltzmann Machines

摘要

Data processing using restricted Boltzmann machines is described, for example, to pre-process continuous data and provide binary outputs. In embodiments, restricted Boltzmann machines based on either Gaussian distributions or Beta distributions are described which are able to learn and model both the mean and variance of data. In some embodiments, a stack of restricted Boltzmann machines are connected in series with outputs of one restricted Boltzmann machine providing input to the next in the stack and so on. Embodiments describe how training for each machine in the stack may be carried out efficiently and the combined system used for one of a variety of applications such as data compression, object recognition, image processing, information retrieval, data analysis and the like.