title: The Singular Values of Convolutional Layers
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%. 
authors: Hanie Sedghi Vineet Gupta Philip M. Long
hIndex: Philip M. Long 42