Question: A type of Autoencoder that aims to generate a compressed and robust representation by applying a sparsity penalty to the hidden units. This sparsity constraint

A type of Autoencoder that aims to generate a compressed and robust representation by applying a sparsity penalty to the hidden units. This sparsity constraint forces the network to activate only a small number of neurons. Answer the following questions related to this Autoencoder: How and exactly on which components of the Autoencoder is the sparsity penalty applied? Explain this topic with the formula for the sparsity penalty. Briefly explain the difference between an Undercomplete Autoencoder and a Sparse Autoencoder. Can batch normalization be used in a Sparse Autoencoder? Explain.

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