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On Lipschitz Bounds of General Convolutional Neural Networks
[article]
2018
arXiv
pre-print
Preserved Fulltext
Many convolutional neural networks (CNNs) have a feed-forward structure. In this paper, a linear program that estimates the Lipschitz bound of such CNNs is proposed. Several CNNs, including the scattering networks, the AlexNet and the GoogleNet, are studied numerically and compared to the theoretical bounds. Next, concentration inequalities of the output distribution to a stationary random input signal expressed in terms of the Lipschitz bound are established. The Lipschitz bound is further
arXiv:1808.01415v1
fatcat:f5fkbyaiobhe3jfgcfuw4sunom