Maximum-EntropyAdversarialDataAugmentation forImprovedGeneralizationandRobustness: SupplementaryMaterial

Neural Information Processing Systems 

LetZ bearandomvariable(continuousordiscrete), and Y be a random variable with a finite set of outcomesY. Following the guidance of [3], we first assume a family of probability densities over the latent variablesθparameterized byψ,i.e.,q(θ|ψ). We use SGD for both minimization and maximization.

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