177 citations · 213 across the 4 of their papers we have counts for
4 papers
Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM
Sheng Lin, Xiaolong Ma, Shaokai Ye +3
Weight quantization is one of the most important techniques of Deep Neural Networks (DNNs) model compression method. A recent work using systematic framework of DNN weight quantiza…
26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone
Wei Niu, Xiaolong Ma, Yanzhi Wang +1
With the rapid emergence of a spectrum of high-end mobile devices, many applications that required desktop-level computation capability formerly can now run on these devices withou…
ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning
Xiaolong Ma, Geng Yuan, Sheng Lin +3
The state-of-art DNN structures involve high computation and great demand for memory storage which pose intensive challenge on DNN framework resources. To mitigate the challenges,…
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Caiwen Ding, Siyu Liao, Yanzhi Wang +13
Large-scale deep neural networks (DNNs) are both compute and memory intensive. As the size of DNNs continues to grow, it is critical to improve the energy efficiency and performanc…