Weightless: Lossy Weight Encoding For Deep Neural Network Compression

Weightless: Lossy Weight Encoding For Deep Neural Network Compression

13 November 2017

Michael Mitzenmacher

Alexander M. Rush

David Brooks

Papers citing "Weightless: Lossy Weight Encoding For Deep Neural Network Compression"

4 / 4 papers shown

Title
Compacting Deep Neural Networks for Internet of Things: Methods and Applications Ke Zhang Hanbo Ying Hongning Dai Lin Li Yuangyuang Peng Keyi Guo Hongfang Yu 28 38 0 20 Mar 2021
T-Basis: a Compact Representation for Neural Networks Anton Obukhov M. Rakhuba Stamatios Georgoulis Menelaos Kanakis Dengxin Dai Luc Van Gool 41 27 0 13 Jul 2020
Bringing Giant Neural Networks Down to Earth with Unlabeled Data Yehui Tang Shan You Chang Xu Boxin Shi Chao Xu 24 11 0 13 Jul 2019
DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression Sian Jin Sheng Di Xin Liang Jiannan Tian Dingwen Tao Franck Cappello AI4CE 24 59 0 26 Jan 2019