Towards Efficient Training for Neural Network Quantization

Towards Efficient Training for Neural Network Quantization

21 December 2019

Linjie Yang

Papers citing "Towards Efficient Training for Neural Network Quantization"

8 / 8 papers shown

Title
Nearly Lossless Adaptive Bit Switching Haiduo Huang Zhenhua Liu Tian Xia Wenzhe zhao Pengju Ren MQ 63 0 0 03 Feb 2025
AdaQAT: Adaptive Bit-Width Quantization-Aware Training Cédric Gernigon Silviu-Ioan Filip Olivier Sentieys Clément Coggiola Mickael Bruno 23 2 0 22 Apr 2024
PIM-QAT: Neural Network Quantization for Processing-In-Memory (PIM) Systems Qing Jin Zhiyu Chen J. Ren Yanyu Li Yanzhi Wang Kai-Min Yang MQ 15 2 0 18 Sep 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 25 11 0 11 Aug 2022
Teachers Do More Than Teach: Compressing Image-to-Image Models Qing Jin Jian Ren Oliver J. Woodford Jiazhuo Wang Geng Yuan Yanzhi Wang Sergey Tulyakov 39 54 0 05 Mar 2021
Loss Aware Post-training Quantization Yury Nahshan Brian Chmiel Chaim Baskin Evgenii Zheltonozhskii Ron Banner A. Bronstein A. Mendelson MQ 28 163 0 17 Nov 2019
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks Ahmed T. Elthakeb Prannoy Pilligundla Fatemehsadat Mireshghallah Amir Yazdanbakhsh H. Esmaeilzadeh MQ 55 68 0 05 Nov 2018
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 233 348 0 14 Jun 2018