Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

Deep learning network compression techniques have emerged as a crucial research area, aiming to reduce the computational and storage requirements of neural networks ...