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Neural networks are easily fooled, provided you know how to fool them. Consider a linear network with an input layer and an output layer, which has an error function E (we don't need hidden layers to show how to fool a network). For a given input image x, E measures the (squared) difference between the network's output y and the desired (correct) output. ...


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