Model compression as constrained optimization, with application to neural nets. Part II: quantization

13 July 2017

Papers citing "Model compression as constrained optimization, with application to neural nets. Part II: quantization"

8 / 8 papers shown

Title
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee Chenyang Li Jihoon Chung Mengnan Du Haimin Wang Xianlian Zhou Bohao Shen 33 1 0 13 Mar 2023
Hyperspherical Quantization: Toward Smaller and More Accurate Models Dan Liu X. Chen Chen-li Ma Xue Liu MQ 27 3 0 24 Dec 2022
AskewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks Louis Leconte S. Schechtman Eric Moulines 29 4 0 07 Nov 2022
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression Yuezhou Sun Wenlong Zhao Lijun Zhang Xiao Liu Hui Guan Matei A. Zaharia 26 0 0 19 Nov 2021
And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock Armand Joulin Rémi Gribonval Benjamin Graham Hervé Jégou MQ 29 149 0 12 Jul 2019
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks Penghang Yin Shuai Zhang J. Lyu Stanley Osher Y. Qi Jack Xin MQ 36 61 0 15 Aug 2018
A Survey on Methods and Theories of Quantized Neural Networks Yunhui Guo MQ 27 230 0 13 Aug 2018
BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights Penghang Yin Shuai Zhang J. Lyu Stanley Osher Y. Qi Jack Xin MQ 22 78 0 19 Jan 2018