Data Dependent Randomized Smoothing

Motasem Alfarra
Motasem Alfarra
Adel Bibi
Adel Bibi
Cited by: 1|Views2

Abstract:

Randomized smoothing is a recent technique that achieves state-of-art performance in training certifiably robust deep neural networks. While the smoothing family of distributions is often connected to the choice of the norm used for certification, the parameters of the distributions are always set as global hyper parameters independent ...More

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