Autoencoder in Autoencoder Networks

Modeling complex correlations on multiview data is still challenging, especially for high-dimensional features with possible noise. To address this issue, we propose a novel unsupervised multiview representation learning (UMRL) algorithm, termed autoencoder in autoencoder networks (AE2-Nets). The pr...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 35; no. 2; pp. 2263 - 2275
Main Authors:	Zhang, Changqing, Geng, Yu, Han, Zongbo, Liu, Yeqing, Fu, Huazhu, Hu, Qinghua
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.02.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Bidirectional encoding Coding Complementarity complete representation Correlation Data mining Degradation Encoding Feature extraction Information processing Kernel Machine learning multiview representation learning Networks Representation learning Representations
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!