Second-Order Methods for Neural Networks

This volume aims to develop understanding of theoretical and practical issues involved in the development of efficient MLP training strategies, and to describe and evaluate the performance of a wide range of specific training algorithm. Particular emphasis is given to the development of methods which have a strong theoretical foundation, rather than heuristic, "rule of thumb" training strategies. "Second order methods for neural networks" should be of interest to academic researchers and postgraduate students working with neural networks (especially supervised learning with multi-layer perceptrons), industrial researchers and programmers developing neural network software, and professionals using neural networks as optimisation tools.