Deep pretraining before AlexNet: the table is set
Before 2012, Hinton, Bengio, and LeCun pushed greedy pretraining, autoencoders, and evidence that deep nets could learn.
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Before 2012, Hinton, Bengio, and LeCun pushed greedy pretraining, autoencoders, and evidence that deep nets could learn.
Rumelhart, Hinton, and Williams popularized gradient descent via error backpropagation in multilayer networks.