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AskewSGD : An Annealed interval-constrained Optimisation method to train
  Quantized Neural Networks

AskewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks

7 November 2022
Louis Leconte
S. Schechtman
Eric Moulines
ArXivPDFHTML

Papers citing "AskewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks"

5 / 5 papers shown
Title
Orthogonal Directions Constrained Gradient Method: from non-linear
  equality constraints to Stiefel manifold
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold
S. Schechtman
D. Tiapkin
Michael Muehlebach
Eric Moulines
19
6
0
16 Mar 2023
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural
  Networks
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks
Huu Le
R. Høier
Che-Tsung Lin
Christopher Zach
40
15
0
06 Dec 2021
Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators
Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators
Alexander Shekhovtsov
MQ
15
4
0
07 Oct 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Tailin Liang
C. Glossner
Lei Wang
Shaobo Shi
Xiaotong Zhang
MQ
124
665
0
24 Jan 2021
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
279
39,083
0
01 Sep 2014
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