Convergence of a Gradient-Based Learning Algorithm With Penalty for Ridge Polynomial Neural Networks

Recently there have been renewed interests in high order neural networks (HONNs) for its powerful mapping capability. Ridge polynomial neural network (RPNN) is an important kind of HONNs, which always occupies a key position as an efficient instrument in the tasks of classification or regression. In...

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Bibliographic Details
Published in:	IEEE access Vol. 9; pp. 28742 - 28752
Main Authors:	Fan, Qinwei, Peng, Jigen, Li, Haiyang, Lin, Shoujin
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Biological neural networks Convergence high order neural networks Input variables Machine learning Neural networks Polynomials Regression analysis Regularization ridge polynomial neural network Smoothing smoothing Group Lasso Smoothing methods Theorems Training
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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