Backpropagation

By P. Munro. 2010

137 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (2015, methodology): “PReLU can be trained using backpropagation [17] and optimized simultaneously with other layers.”
Conditional Random Fields as Recurrent Neural Networks (2015, methodology): “these parameters in a single iteration was described in Section 4, they can be learnt in the RNN setting using the standard back-propagation through time algorithm [48, 40].”
Spatio-temporal video autoencoder with differentiable memory (2015, background): “Motivated by these two shortcomings, we focus on reducing the supervision effort required to train recurrent neural networks, which are known for their ability to handle sequential input data Williams & Zipser (1995); Hochreiter et al. (2000).”
A Survey of Monte Carlo Tree Search Methods (2012, unknown): “Proof-number search (PNS) is a standard AI technique for proving game-theoretic values, typically used for endgame solvers, in which terminal states are considered to be proven wins or losses and deductions chained backwards from these [4].”