Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective
Adhyyan Narang,
Vidya Muthukumar,
Anant Sahai
Abstract:State-of-the-art deep learning classifiers are heavily overparameterized with respect to the amount of training examples and observed to generalize well on "clean" data, but be highly susceptible to infinitesmal adversarial perturbations. In this paper, we identify an overparameterized linear ensemble, that uses the "lifted" Fourier feature map, that demonstrates both of these behaviors 1 . The input is one-dimensional, and the adversary is only allowed to perturb these inputs and not the non-linear features d… Show more
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