This paper deals with the computational aspects of neural networks. Specifically, it is suggested that the now traditional method of backpropagation (BP) may not be the most appropriate basis for learning. The argument is based on the known deficiencies of gradient descent methods, of which BP...

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is...