Generalization of a Parametric Learning Rule
Samy Bengio, Yoshua Bengio, J. Cloutier, Jan Gecsei · 1993
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.