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Backpropagation was first applied to Neural Networks over 30 years ago [Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (8 October 1986). "Learni
by eliben 9y ago
Backpropagation was first applied to Neural Networks over 30 years ago
[Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (8 October 1986). "Learning representations by back-propagating errors". Nature]
- nightski 9y agoNot to deep nets iirc, which was one of the advancements.
- pedrosorio 9y agoThe GP implies that was not tried before: "There was a revolution, when they started using backpropogation to optimize the gradient search". "Back-propagation allowed researchers to train supervised deep artificial neural networks from scratch, initially with little success. Hochreiter's diploma thesis of 1991[1][2] formally identified the reason for this failure in the "vanishing gradient problem", which not only affects many-layered feedforward networks,[3] but also recurrent networks." https://en.m.wikipedia.org/wiki/Vanishing_gradient_problem https://en.m.wikipedia.org/wiki/Vanishing_gradient_problem