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Consider an autoencoder with h hidden units, and input to the autoencoder is a set of d - dimensional unlabeled data, x i = 1
Consider an autoencoder with hidden units, and input
to the autoencoder is a set of dimensional unlabeled data, where
denotes the weight matrix between the input layer and the hidden layer
and denotes the weight matrix between the hidden layer and the output
layer. denotes the activation function for hidden layer, and is the activation
function for the output layer.
hat
hathat
is the reconstruction error for example is
the total reconstruction error. We add to the input and hidden layer so that no
bias term is required.
Compute and
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