A New Fast Training Algorithm for Autoencoder Neural Networks based on Extreme Learning Machine

Autoencoders are neural networks that are characterized by having the same inputs and outputs. This kind of Neural Networks aim to estimate a nonlinear transformation whose parameters allow to represent the input patterns to the network. The Extreme Learning Machine (ELM-AE) Autoencoders have random...

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Bibliographic Details

Published in:	2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA) pp. 1 - 7
Main Authors:	Vasquez-Coronel, Jose A., Mora, Marco, Vilches, Karina, Silva-Pavez, Fabian, Torres-Gonzalez, Italo, Barria-Valdevenito, Pedro
Format:	Conference Proceeding
Language:	English
Published:	IEEE 24.10.2022
Subjects:	Autoencoder Extreme Learning Machine Extreme learning machines Feature extraction Linear systems Machine learning Machine learning algorithms Neurons Shrinkage-thresholding algorithms Training
Online Access:	Get full text
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