Compressed Superposition of Neural Networks for Deep Learning in Edge Computing

This paper investigates a combination of the two recently proposed techniques: superposition of multiple neural networks into one and neural network compression. We show that these two techniques can be successfully combined to deliver a great potential for trimming down deep convolutional neural networks. The work can be relevant in the context of implementing deep learning on low-end computing d...