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Fast Adjustable Threshold For Uniform Neural Network Quantization
  (Winning solution of LPIRC-II)

Fast Adjustable Threshold For Uniform Neural Network Quantization (Winning solution of LPIRC-II)

19 December 2018
A. Goncharenko
Andrey Denisov
S. Alyamkin
Evgeny Terentev
    MQ
ArXivPDFHTML

Papers citing "Fast Adjustable Threshold For Uniform Neural Network Quantization (Winning solution of LPIRC-II)"

4 / 4 papers shown
Title
Quantune: Post-training Quantization of Convolutional Neural Networks
  using Extreme Gradient Boosting for Fast Deployment
Quantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment
Jemin Lee
Misun Yu
Yongin Kwon
Teaho Kim
MQ
19
17
0
10 Feb 2022
Self-Compression in Bayesian Neural Networks
Self-Compression in Bayesian Neural Networks
Giuseppina Carannante
Dimah Dera
Ghulam Rasool
N. Bouaynaya
UQCV
BDL
33
5
0
10 Nov 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure
  DNN Accelerators
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators
David Stutz
Nandhini Chandramoorthy
Matthias Hein
Bernt Schiele
AAML
MQ
24
18
0
16 Apr 2021
Post-Training 4-bit Quantization on Embedding Tables
Post-Training 4-bit Quantization on Embedding Tables
Hui Guan
Andrey Malevich
Jiyan Yang
Jongsoo Park
Hector Yuen
MQ
13
32
0
05 Nov 2019
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