Learning Representations by Back-propagating Errors

Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning Representations by Back-propagating Errors. Nature, 323(6088), 533-536.

Type

Journal article

Intellectual base

Primary research

Year

1986

DOI

10.1038/323533a0

Link

https://doi.org/10.1038/323533a0

Cited from

computer_science, mathematics

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Gradient
  • In optimization and machine learning, gradient descent and its stochastic variants (originating with Cauchy and revived for large-scale ML by Robbins-Monro), backpropagation
• Higher Order Function
  • In legal theory this maps to the hierarchy of norms; in machine learning, to the chain rule and backpropagation.

    This sourceBackpropagation as repeated application of the chain rule — composition over differentiable rules.

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