Levenberg-Marquardt and Conjugate Gradient Methods Applied to a High-order Neural Network
The HONEST network is a high order neural network that uses product units and adaptable exponential weights. In this paper, we explore the use of several learning methods with the HONEST network: Levenberg-Marquardt (LM), Conjugate Gradient (CG), Scaled Conjugate Gradient (a technique that combines LM and CG), and resilient propagation (RP). Using a benchmark of 19 datasets, we find that the first three methods mentioned produce lower average test set errors than RP to a statistically significant extent.
I. El-Nabarawy et al., "Levenberg-Marquardt and Conjugate Gradient Methods Applied to a High-order Neural Network," Proceedings of International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers (IEEE), Jan 2013.
The definitive version is available at http://dx.doi.org/10.1109/IJCNN.2013.6707004
2013 International Joint Conference on Neural Networks (IJCNN) (2013: Aug. 4-9, Dallas, TX)
Electrical and Computer Engineering
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