Learning multiple layers of representation.

@article{Hinton2007LearningML,
  title={Learning multiple layers of representation.},
  author={Geoffrey E. Hinton},
  journal={Trends in cognitive sciences},
  year={2007},
  volume={11 10},
  pages={428-34}
}
To achieve its impressive performance in tasks such as speech perception or object recognition, the brain extracts multiple levels of representation from the sensory input. Backpropagation was the first computationally efficient model of how neural networks could learn multiple layers of representation, but it required labeled training data and it did not work well in deep networks. The limitations of backpropagation learning can now be overcome by using multilayer neural networks that contain… CONTINUE READING
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