Generalization of a Parametric Learning Rule
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We proposed in previous work ([1, 2]) a method to find new learning rules for neural networks, considering them as parametric functions and using any standard optimization method (such as genetic algorithms, gradient descent, and simulated annealing) to select the parameters.
[1] Yoshua Bengio,et al. Learning a synaptic learning rule , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.