Comparison of gradient based training algorithms for multilayer perceptrons

The training speed of batch backpropagation using steepest descent, conjugate gradient and quasi-Newton algorithm for a feedforward neural network are compared. Results illustrating the advantages of the Hessian based techniques are given and issues affecting speed discussed.<
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