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The Singular Values of Convolutional Layers

2018-05-26ICLR 2019Code Available0· sign in to hype

Hanie Sedghi, Vineet Gupta, Philip M. Long

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Abstract

We characterize the singular values of the linear transformation associated with a standard 2D multi-channel convolutional layer, enabling their efficient computation. This characterization also leads to an algorithm for projecting a convolutional layer onto an operator-norm ball. We show that this is an effective regularizer; for example, it improves the test error of a deep residual network using batch normalization on CIFAR-10 from 6.2\% to 5.3\%.

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