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Modulating Regularization Frequency for Efficient Compression-Aware
  Model Training

Modulating Regularization Frequency for Efficient Compression-Aware Model Training

5 May 2021
Dongsoo Lee
S. Kwon
Byeongwook Kim
Jeongin Yun
Baeseong Park
Yongkweon Jeon
ArXivPDFHTML

Papers citing "Modulating Regularization Frequency for Efficient Compression-Aware Model Training"

3 / 3 papers shown
Title
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural
  Networks
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
Incremental Network Quantization: Towards Lossless CNNs with
  Low-Precision Weights
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights
Aojun Zhou
Anbang Yao
Yiwen Guo
Lin Xu
Yurong Chen
MQ
316
1,047
0
10 Feb 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,888
0
15 Sep 2016
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