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Quickprop

Quickprop is an iterative method for determining the minimum of the loss function of an artificial neural network, following an algorithm inspired by… 
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Related topics

Related topics

7 relations
Artificial neural networkArtificial neuronBackpropagationGradient

Broader (1)

Computational neuroscience

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Recognition of Handwritten Images Using Multilayer Neural Networks
The architecture and training algorithms of multilayer neural networks are considered. A description of the implemented NeuralNet… 
2015
2015
GENOUD-BP: A novel training algorithm for artificial neural networks
BP Algorithm, as a well-known training method for artificial neural network, has been widely used in all the main fields of… 
2008
2008
Parallelizing neural network training for cluster systems
We present a technique for parallelizing the training of neural networks. Our technique is designed for parallelization on a… 
2004
2004
Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons
2003
2003
Random weights search in compressed neural networks using overdetermined pseudoinverse
Proposed algorithm exhibits 2 significant advantages: easier hardware implementation and robust convergence. Proposed algorithm… 
2000
2000
Globally Convergent Modification of the Quickprop Method
A mathematical framework for the convergence analysis of the well-known Quickprop method is described. Furthermore, we propose a… 
1999
1999
Convergence analysis of the Quickprop method
A mathematical framework for the convergence analysis of the well known Quickprop method is described. The convergence of this… 
1996
1996
SSME parameter model input selection using genetic algorithms
Genetic algorithms are used for the systematic selection of inputs for a parameter modeling system based on a neural network… 
1992
1992
Implementation of back-propagation neural networks with MatLab
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1 . BACK PROPAGATION ALGORITHM USING MATLAB… 
1989
1989
Speaker-independent recognition of connected utterances using recurrent and non-recurrent neural networks
Connectionist learning procedures are applied to the task of speaker-independent continuous speech recognition, creating a system… 
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