Deep Autoencoders (Hinton & Salakhutdinov, Science 2006)
	• Autoencoders always looked like a really nice way to do non-linear dimensionality reduction: – They provide mappings both ways – The learning time and memory both scale linearly with the number of training cases. – The final model is compact and fast. • But it turned out to be very very difficult to optimize deep autoencoders using backprop. – We now have a much better way to optimize them.