Reduced-Order Modeling of Deep Neural Networks

We introduce a new method for speeding up the inference of deep neural networks. It is somewhat inspired by reduced-order modeling techniques dynamical systems. The cornerstone proposed maximum volume algorithm. demonstrate efficiency on networks pre-trained different datasets. show that in many practical cases it possible to replace convolutional layers with much smaller fully-connected relatively small drop accuracy.