2 papers
cs.NE2020
Procrustes: a Dataflow and Accelerator for Sparse Deep Neural Network Training
Dingqing Yang, Amin Ghasemazar, Xiaowei Ren +3
The success of DNN pruning has led to the development of energy-efficient inference accelerators that support pruned models with sparse weight and activation tensors. Because the m…
cs.LG2018
Full deep neural network training on a pruned weight budget
Maximilian Golub, Guy Lemieux, Mieszko Lis
We introduce a DNN training technique that learns only a fraction of the full parameter set without incurring an accuracy penalty. To do this, our algorithm constrains the total nu…