2018
Weightless: Lossy weight encoding for deep neural network compression
ICML 2018oral
The large memory requirements of deep neural networks limit their deployment and adoption on many devices. Model compression methods effectively reduce the memory requirements of these models, usually through applying transformations such as weight pruning or quantization. In this paper, we present…