发帖
雷达卡
Skew Orthogonal Convolutions
Sahil Singla 1 Soheil Feizi 1
Abstract adversarial robustness (Cisse et al., 2017; Szegedy et al.,
2014) and interpretable gradients (Tsipras et al., 2018). The
Training convolutional neural networks with a Lipschitz constant also upper bounds the change in gra-
Lipschitz constraint under the l2 norm is useful for dient norm during backpropagation and can thus prevent
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