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Shen et al., 2019 - Google Patents

Training auto-encoders effectively via eliminating task-irrelevant input variables

Shen et al., 2019

View PDF
Document ID
15744584091228958675
Author
Shen H
Li D
Wu H
Zang Z
Publication year
Publication venue
International Journal of Computational Science and Engineering

External Links

Snippet

Auto-encoders are often used as building blocks of deep network classifiers to learn feature extractors, but task-irrelevant information in the input data may lead to bad extractors and result in poor generalisation performance of the network. In this paper, via dropping the task …
Continue reading at arxiv.org (PDF) (other versions)

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