Deep Learning Reading Group: Deep Compression

The next paper from our reading group is by Song Han, Huizi Mao, and William J. Dally. It won the best paper award at ICLR 2016. It details three methods of compressing a neural network in order to reduce the size of the network on disk, improve performance, and decrease run time. Pre-trained convolutional neural networks are too large for mobile devices: AlexNet is 240 MB and VGG-16 is over 552 MB. This seems small when compared to a music library or large video, but the difference is that the networks reside in memory when running.