Cross-covariance regularized autoencoders for nonredundant sparse feature representation

We propose a new feature representation algorithm using cross-covariance in the context of deep learning. Existing feature representation algorithms based on the sparse autoencoder and nonnegativity-constrained autoencoder tend to produce duplicative encoding and decoding receptive fields, which lea...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 316; pp. 49 - 58
Main Authors:	Chen, Jie, Wu, ZhongCheng, Zhang, Jun, Li, Fang, Li, WenJing, Wu, ZiHeng
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 17.11.2018
Subjects:	Autoencoder Cross-covariance Deep learning Feature representation Receptive fields Deep learning Receptive fields Cross-covariance Feature representation Autoencoder
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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