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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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Topic mentions per year

Topic mentions per year

1985-2017
051019852017

Related topics

Related topics

8 relations
Activation functionBackpropagationCatastrophic interferenceFeedforward neural network
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Related mentions per year

Related mentions per year

1936-2018
19401960198020002020
Delta rule
Machine learning
Gradient descent
Perceptron
Backpropagation
Feedforward neural network

Papers overview

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2009
2009
Performance Comparison of Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron) algorithms in Neural Networks
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
A learning rule for very simple universal approximators consisting of a single layer of perceptrons
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
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning… (More)
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1997
1997
Factor Analysis Using Delta-Rule Wake-Sleep Learning
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
Extensions to the delta rule for associative learning
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
Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta
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
A norm selection criterion for the generalized delta rule
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
When is the generalized delta rule a learning rule? a physical analogy
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
Increased rates of convergence through learning rate adaptation
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
The delta rule development system for speech synthesis from text
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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