Linear programming algorithm for neural networks

Abstract A new learning algorithm for feedforward neural networks based on linear programming is introduced. This alternative to back-propagation gives faster and more reliable learning on reasonably sized examples. Extensions of the method for efficient (approximate) implementations in large networks are considered.

[1]  Robert Hecht-Nielsen,et al.  Theory of the backpropagation neural network , 1989, International 1989 Joint Conference on Neural Networks.

[2]  W. Krauth,et al.  Learning algorithms with optimal stability in neural networks , 1987 .

[3]  Marvin Minsky,et al.  Perceptrons: expanded edition , 1988 .

[4]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[5]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.