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Backpropagation

Known as: Error back-propagation, Backpropogation, Back prop 
Backpropagation, an abbreviation for "backward propagation of errors", is a common method of training artificial neural networks used in conjunction… 
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AI winterALOPEXAdaBoostAutoencoder

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2001
Highly Cited
2001
A guide to recurrent neural networks and backpropagation
This paper provides guidance to some of the concepts surrounding recurrent neural networks. Contrary to feedforward networks… 
Highly Cited
1996
Highly Cited
1996
The Backpropagation Algorithm
We saw in the last chapter that multilayered networks are capable of computing a wider range of Boolean functions than networks… 
Highly Cited
1995
Highly Cited
1995
Backpropagation: the basic theory
Since the publication of the PDP volumes in 1986, learning by backpropagation has become the most popular method of training… 
Highly Cited
1995
Highly Cited
1995
The Influence of the Sigmoid Function Parameters on the Speed of Backpropagation Learning
Sigmoid function is the most commonly known function used in feed forward neural networks because of its nonlinearity and the… 
Highly Cited
1992
Highly Cited
1992
A Practical Bayesian Framework for Backpropagation Networks
A quantitative and practical Bayesian framework is described for learning of mappings in feedforward networks. The framework… 
Highly Cited
1992
Highly Cited
1992
On the Problem of Local Minima in Backpropagation
The authors propose a theoretical framework for backpropagation (BP) in order to identify some of its limitations as a general… 
Highly Cited
1991
Highly Cited
1991
The complex backpropagation algorithm
The backpropagation (BP) algorithm that provides a popular method for the design of a multilayer neural network to include… 
Review
1990
Review
1990
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation
Fundamental developments in feedforward artificial neural networks from the past thirty years are reviewed. The history… 
Highly Cited
1990
Highly Cited
1990
Backpropagation is Sensitive to Initial Conditions
This paper explores the effect of initial weight selection on feed-forward networks learning simple functions with the back… 
Review
1989
Review
1989
Theory of the backpropagation neural network
  • R. Hecht-Nielsen
  • International Joint Conference on Neural…
  • 1989
  • Corpus ID: 5691634
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