Blended Coarse Gradient Descent for Full Quantization of Deep Neural
Networks

Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks

15 August 2018

Stanley Osher

Papers citing "Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks"

13 / 13 papers shown

Title
AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks Cheng Gong Ye Lu Surong Dai Deng Qian Chenkun Du Tao Li MQ 27 0 0 07 Apr 2023
RedBit: An End-to-End Flexible Framework for Evaluating the Accuracy of Quantized CNNs A. M. Ribeiro-dos-Santos João Dinis Ferreira O. Mutlu G. Falcão MQ 13 1 0 15 Jan 2023
Elastic Significant Bit Quantization and Acceleration for Deep Neural Networks Cheng Gong Ye Lu Kunpeng Xie Zongming Jin Tao Li Yanzhi Wang MQ 22 7 0 08 Sep 2021
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 16 5 0 31 Aug 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey Tailin Liang C. Glossner Lei Wang Shaobo Shi Xiaotong Zhang MQ 124 673 0 24 Jan 2021
Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks Jonathan Ashbrock A. Powell MQ 20 5 0 25 Aug 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 24 5 0 21 Aug 2020
Binary Neural Networks: A Survey Haotong Qin Ruihao Gong Xianglong Liu Xiao Bai Jingkuan Song N. Sebe MQ 48 457 0 31 Mar 2020
Towards Unified INT8 Training for Convolutional Neural Network Feng Zhu Ruihao Gong F. Yu Xianglong Liu Yanfei Wang Zhelong Li Xiuqi Yang Junjie Yan MQ 27 151 0 29 Dec 2019
Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks Ruihao Gong Xianglong Liu Shenghu Jiang Tian-Hao Li Peng Hu Jiazhen Lin F. Yu Junjie Yan MQ 21 445 0 14 Aug 2019
Learning low-precision neural networks without Straight-Through Estimator(STE) Z. G. Liu Matthew Mattina MQ 19 34 0 04 Mar 2019
$Learning Sparse Neural Networks via $\ell_0$ and T$\ell_1$ by a Relaxed Variable Splitting Method with Application to Multi-scale Curve Classification$ Learning Sparse Neural Networks via $\ell_0$ and T $\ell_1$ by a Relaxed Variable Splitting Method with Application to Multi-scale Curve Classification Fanghui Xue Jack Xin 22 7 0 20 Feb 2019
Relaxed Quantization for Discretized Neural Networks Christos Louizos M. Reisser Tijmen Blankevoort E. Gavves Max Welling MQ 27 131 0 03 Oct 2018