Rprop

Known as: Resilient backpropagation, Resilient propagation 
Rprop, short for resilient backpropagation, is a learning heuristic for supervised learning in feedforward artificial neural networks. This is a… (More)
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2013
2013
Gaussian processes are a powerful tool for non-parametric regression. Training can be realized by maximizing the likelihood of… (More)
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2008
2008
RPROP is a fast BP algorithm in which the weights are adjusted local adaptively and the parameters can be chosen easily. The… (More)
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2005
2005
Gradient-based optimization algorithms are the standard methods for adapting the weights of neural networks. The natural gradient… (More)
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2005
2005
An adaptive learning method for recurrent fuzzy systems is proposed. The method modifies the SARPROP algorithm, originally… (More)
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Highly Cited
2003
Highly Cited
2003
The Rprop algorithm proposed by Riedmiller and Braun is one of the best performing -rst-order learning methods for neural… (More)
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2003
2003
This paper introduces an efficient modification of the Rprop algorithm for training neural networks. The convergence of the new… (More)
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Highly Cited
2000
Highly Cited
2000
The Rprop algorithm proposed by Riedmiller and Braun is one of the best performing first-order learning methods for neural… (More)
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1997
1997
N.K. Treadgold and T.D. Gedeon School of Computer Science & Engineering The University of New South Wales Sydney N.S.W. 2052… (More)
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Highly Cited
1994
Highly Cited
1994
A. General Description Rprop stands for 'Resilient backpropagation' and is a local adaptive learning scheme, performing… (More)
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Highly Cited
1993
Highly Cited
1993
A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure… (More)
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