Improving transfer learning accuracy by reusing Stacked Denoising Autoencoders

Transfer learning is a process that allows reusing a learning machine trained on a problem to solve a new problem. Transfer learning studies on shallow architectures show low performance as they are generally based on hand-crafted features obtained from experts. It is therefore interesting to study...

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Bibliographic Details

Published in:	Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 1380 - 1387
Main Authors:	Kandaswamy, Chetak, Silva, Luis M., Alexandre, Luis A., Sousa, Ricardo, Santos, Jorge M., de Sa, Joaquim Marques
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2014
Subjects:	Computer architecture Deep Learning Error analysis Noise reduction Shape Training Transfer Learning Visualization Yttrium
ISSN:	1062-922X
Online Access:	Get full text
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