Reviews: CNNpack: Packing Convolutional Neural Networks in the Frequency Domain

The technique is fairly natural, since DCTs are routinely used to compress images. However, neural network weight matrices look quite different from images especially in the case of weight decay. They are often sparse, which lends strength to techniques that take advantage of sparsity elementwise rather than sparsity after transformation. This handwaving is backed up by the paper results, which do not exhibit significantly more compression than the P QH baseline. The comparison to only AlexNet and VGG on ImageNet is problematic for judging compression quality, since Inception is significantly smaller than both models. The possibly underconverged non-augmented version on CIFAR-10 is insufficient here, since a better tuned model might be more difficult to compress without losing accuracy.