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Gmelli

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Gmelli

Created page with "A Sparse Autoencoder Network is an autoencoder network that incorporates a sparsity constraint on the hidden units during training, forcing the sparse autoencoder model to learn a sparse representation of the input data. * <B>Context:</B> ** It can (often) implement sparsity using a penalty term in the loss function, such as the Kullback–Leibler Divergence, to limit the number of active neurons. ** It can (often) use k-Spar..."