Whereas before 2006 it appears that deep multilayer neural networks were not successfully trained, since then several algorithms have been shown to successfully train them, with e...
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Abstract. Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, ...
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
Hybrid set of optimally trained feed-forward, Hopfield and Elman neural networks were used as computational tools and were applied to immunoinformatics. These neural networks ena...