Non-Structured DNN Weight Pruning—Is It Beneficial in Any Platform?
Xiaolong Ma(Universidad del Noreste), Yanzhi Wang(Sichuan University), Shaokai Ye(École Polytechnique Fédérale de Lausanne), Sia Huat Tan(Tsinghua University), Zhezhi He(Shanghai Jiao Tong University), Xue Lin(Northeastern University), Xuehai Qian(Tsinghua University), Deliang Fan(Arizona State University), Sheng Lin(Qingdao Agricultural University), Linfeng Zhang(Shanghai Jiao Tong University), Kaisheng Ma(Tsinghua University), Zhengang Li(Northeastern University), Geng Yuan(Northeastern University)
Cited by 99
Related Papers
Multi-animal pose estimation, identification and tracking with DeepLabCut
|Nature Methods|2022|613
CNTFET-Based Design of Ternary Logic Gates and Arithmetic Circuits
|IEEE Transactions on Nanotechnology|2009|599
Incidence, Clinical Course, and Predictors of Prolonged Recovery Time Following Sport-Related Concussion in High School and College Athletes
|Journal of the International Neuropsychological Society|2012|501
A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers
|Lecture notes in computer science|2018|498
Deep Reinforcement Learning for Building HVAC Control
|Unknown|2017|447