I am looking at Autoencoders in keras. They say,

"Autoencoding" is a data compression algorithm where the compression and decompression functions are 1) data-specific, 2) lossy, and 3) learned automatically from examples rather than engineered by a human

My assumption is, because it is lossy, using Autoencoder does not increase the accuracy. Say, I have a seq2seq model for text summarization, if I use Autoencoder I can speed up the training process but it will not increase the accuracy of the model. Is this assumption correct?

Thank you!



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.