We define a discrepancy between probabilistic outputs of the two classifiers p 1 (y|x) and p 2 (y|x).
the formula is: where defines the average absolute difference for K classes, which is: (4) we first fix the generator G and train the classifiers F 1 ,F 2 to detect points near the decision boundary by maximizing their discrepancy.