Does anyone could help me to understand what the autoencoders means?
What we expect is that the outputs are equal to the inputs, then why we need to do that? It doesn't make any sense to me.
I find some interpretation that it learned how to reconstruct the input data, does that mean that we could just pick some of the pixels from the origin picture and then reconstruct the whole original picture? If so, it still makes no sense to me, because the reconstructing part of the model is from the hidden layer to the output layer, we cannot just put the selected data into the hidden layer, cuz the input data of the hidden layer are combinations of the whole raw data from the input layer.
Thanks in advance.