Autoencoders reloaded

In Bourlard and Kamp (Biol Cybern 59(4):291–294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called “auto-associative multilayer perceptrons”) were, in the best case, implementing singular value decomposition (SVD) Golub and Reinsch (Linear algebra,...

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Bibliographic Details
Published in:	Biological cybernetics Vol. 116; no. 4; pp. 389 - 406
Main Authors:	Bourlard, Hervé, Kabil, Selen Hande
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2022 Springer Nature B.V
Subjects:	Artificial neural networks Bioinformatics Biomedical and Life Sciences Biomedicine Coders Complex Systems Computer Appl. in Life Sciences Decomposition Eigenvalues Empirical analysis Feature extraction Linear algebra Machine learning Manifolds (mathematics) Multilayer perceptrons Neural networks Neurobiology Neurosciences Principal components analysis Prospects Singular value decomposition Statistical analysis Deep neural networks Autoencoders Auto-associative multilayer perceptrons Principal component analysis Singular value decomposition
ISSN:	1432-0770, 0340-1200, 1432-0770
Online Access:	Get full text
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