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...
The neural network (NN) models well trained and validated by the same data may exhibit noticeably different predictabilities in applications. This is mainly due to the fact that t...
Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
—The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function represen...
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...