In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in a singleâ€¦Â (More)

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2009

2009

- Mutasem Khalil Sari Alsmadi, Khairuddin Bin Omar, Shahrul Azman Mohd. Noah, Ibrahim Almarashdah
- 2009 IEEE International Advance Computingâ€¦
- 2009

A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriateâ€¦Â (More)

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2008

2008

- Peter Auer, Harald Burgsteiner, Wolfgang Maass
- Neural Networks
- 2008

One may argue that the simplest type of neural networks beyond a single perceptron is an array of several perceptrons in parallelâ€¦Â (More)

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2008

2008

- Peter Carbonetto, Mark W. Schmidt, Nando de Freitas
- NIPS
- 2008

The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learningâ€¦Â (More)

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1997

1997

- Radford M. Neal, Peter Dayan
- Neural Computation
- 1997

We describe a linear network that models correlations between real-valued visible variables using one or more real-valued hiddenâ€¦Â (More)

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1995

1995

- John K. Kruschke, Amy L. Bradley, Michael L. Kalish, A. da CÃ¢mara Machado, Sarah Countryman, Matthew Durkee
- 1995

The delta rule of associative learning has recently been used in several models of human category learning, and applied toâ€¦Â (More)

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Highly Cited

1992

Highly Cited

1992

- Richard S. Sutton
- AAAI
- 1992

Appropriate bias is widely viewed as the key to efficient learning and generalization. I present a new algorithm, the Incrementalâ€¦Â (More)

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1991

1991

- Pietro Burrascano
- IEEE Trans. Neural Networks
- 1991

The derivation of a supervised training algorithm for a neural network implies the selection of a norm criterion which gives aâ€¦Â (More)

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1988

1988

- Janell Pemberton, J. J. Vidal
- IEEE 1988 International Conference on Neuralâ€¦
- 1988

The authors show that under some conditions the weights and threshold obtained under the linear generalized delta rule can beâ€¦Â (More)

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Highly Cited

1988

Highly Cited

1988

- Robert A. Jacobs
- Neural Networks
- 1988

While there exist many techniques for finding the parameters that minimize an error function, only those methods that solelyâ€¦Â (More)

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1985

1985

- S.R. Hertz, Jim Kadin, K J Karplus
- Proceedings of the IEEE
- 1985

Progress in speech synthesis has been hampered by the lack of rule-writing tools of sufficient flexibility and power. This paperâ€¦Â (More)

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