Autoencoder


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An autoencoder is a Neural network that tries to reconstruct its own input through a bottleneck. It’s a dimensionality reduction technique.

Since it doesn’t require labeling, it’s an unsupervised machine learning method.

A linear autoencoder (an autoencoder without activation functions) is roughly equivalent to a PCA.

Sparse autoencoder

A sparse autoencoder, or an SAE, is an autoencoder with a sparsity term added to the loss. Usually this is an L1 loss to encourage a representation with mostly 0 values.

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@article{yaltirakli,
  title   = "Autoencoder",
  author  = "Yaltirakli, Gokberk",
  journal = "gkbrk.com",
  year    = "2024",
  url     = "https://www.gkbrk.com/autoencoder"
}
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IEEE Citation
Gokberk Yaltirakli, "Autoencoder", October, 2024. [Online]. Available: https://www.gkbrk.com/autoencoder. [Accessed Oct. 10, 2024].
APA Style
Yaltirakli, G. (2024, October 10). Autoencoder. https://www.gkbrk.com/autoencoder
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Gokberk Yaltirakli, Autoencoder, GKBRK.COM (Oct. 10, 2024), https://www.gkbrk.com/autoencoder

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