Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
We present a system for regression using MLP neural networks with hyperbolic tangent functions in the input, hidden and output layer. The activation functions in the input and outp...
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...
Ideally computer pattern recognition systems should be insensitive to scaling, translation, distortion and rotation. Many neural network models have been proposed to address this ...
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...