Delta rule

In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in a single… (More)
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1985-2017
051019852017

Papers overview

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2009
2009
A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate… (More)
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2008
2008
One may argue that the simplest type of neural networks beyond a single perceptron is an array of several perceptrons in parallel… (More)
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2008
2008
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning… (More)
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1997
1997
We describe a linear network that models correlations between real-valued visible variables using one or more real-valued hidden… (More)
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1995
1995
The delta rule of associative learning has recently been used in several models of human category learning, and applied to… (More)
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Highly Cited
1992
Highly Cited
1992
Appropriate bias is widely viewed as the key to efficient learning and generalization. I present a new algorithm, the Incremental… (More)
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1991
1991
The derivation of a supervised training algorithm for a neural network implies the selection of a norm criterion which gives a… (More)
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1988
1988
The authors show that under some conditions the weights and threshold obtained under the linear generalized delta rule can be… (More)
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Highly Cited
1988
Highly Cited
1988
While there exist many techniques for finding the parameters that minimize an error function, only those methods that solely… (More)
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1985
1985
Progress in speech synthesis has been hampered by the lack of rule-writing tools of sufficient flexibility and power. This paper… (More)
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