Fine-tuning Stacked AEs
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+ | === Introduction === | ||
+ | Fine tuning is a strategy that is commonly used to reduce the run time of a stacked autoencoder. It involves viewing all layers of a stacked autoencoder as a single model. | ||
+ | === Strategy === | ||
+ | Conceptually, fine tuning is quite simple. In order to view all layers of a stacked autoencoder as a single model, the gradients at each step are computed using back propagation [LINK], as discussed in the sparse autoencoder section. |