An objective function that encourages an encoder to have the minimum overall Euclidean reconstruction error is shown to lead to encoders that can be implemented using functions that depend only in a piece-wise linear fashion on the input vector.From the neural network viewpoint, the optimal form of the probability that each neuron is the next one to fire is a piecewise linear function of the input vector.
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