Embedded stacked group sparse autoencoder ensemble with L1 regularization and manifold reduction

Learning useful representations from original features is a key issue in classification tasks. Stacked autoencoders (SAEs) are easy to understand and realize, and they are powerful tools that learn deep features from original features, so they are popular for classification problems. The deep featur...

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Bibliographic Details

Published in:	Applied soft computing Vol. 101; p. 107003
Main Authors:	Li, Yongming, Lei, Yan, Wang, Pin, Jiang, Mingfeng, Liu, Yuchuan
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.03.2021
Subjects:	Embedded deep learning Embedded stacked group sparse autoencoder (ESGSAE) Ensemble learning Feature fusion Weighted local discriminant preservation projection (w_LPPD) Embedded stacked group sparse autoencoder (ESGSAE) Embedded deep learning Feature fusion Ensemble learning Weighted local discriminant preservation projection (w_LPPD)
ISSN:	1568-4946, 1872-9681
Online Access:	Get full text
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