Prehistory — From Neural Networks to the TransformerGeoffrey Hinton, Simon Osindero, Yee-Whye TehGeoffrey Hinton

A Fast Learning Algorithm for Deep Belief Nets

A Fast Learning Algorithm for Deep Belief Nets — greedy layer-wise pretraining followed by fine-tuning

Why it matters

Showed once again that deep networks can be trained, sparking the revival of deep learning in the 2000s

Source — Primary sources first; secondary reports are labelled “Press”

Officialcs.toronto.eduhttps://www.cs.toronto.edu/~hinton/absps/fastnc.pdf

Added in Week 35, 2026 · See that week

Nearby on the same axis

Greedy Layer-Wise Training of Deep NetworksPaperA Neural Probabilistic Language ModelOfficialImageNet: A Large-Scale Hierarchical Image DatabaseOfficialLarge-scale Deep Unsupervised Learning using Graphics ProcessorsOfficial