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Automated Pruning for Deep Neural Network Compression
v1v2 (latest)

Automated Pruning for Deep Neural Network Compression

5 December 2017
Franco Manessi
A. Rozza
Luigi Celona
Paolo Napoletano
Raimondo Schettini
ArXiv (abs)PDFHTML

Papers citing "Automated Pruning for Deep Neural Network Compression"

14 / 14 papers shown
Optimizing Dense Feed-Forward Neural Networks
Optimizing Dense Feed-Forward Neural NetworksNeural Networks (Neural Netw.), 2023
Luis Balderas
Miguel Lastra
José M. Benítez
219
11
0
16 Dec 2023
SD-Conv: Towards the Parameter-Efficiency of Dynamic Convolution
SD-Conv: Towards the Parameter-Efficiency of Dynamic ConvolutionIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Shwai He
Chenbo Jiang
Daize Dong
Liang Ding
265
6
0
05 Apr 2022
Solving hybrid machine learning tasks by traversing weight space
  geodesics
Solving hybrid machine learning tasks by traversing weight space geodesics
G. Raghavan
Matt Thomson
175
0
0
05 Jun 2021
Compacting Deep Neural Networks for Internet of Things: Methods and
  Applications
Compacting Deep Neural Networks for Internet of Things: Methods and ApplicationsIEEE Internet of Things Journal (IEEE IoT Journal), 2021
Ke Zhang
Hanbo Ying
Hongning Dai
Lin Li
Yuangyuang Peng
Keyi Guo
Hongfang Yu
301
48
0
20 Mar 2021
Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls
  for Network Pruning
Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls for Network Pruning
K. Azarian
Fatih Porikli
CVBM
105
0
0
19 Mar 2021
Automated Model Compression by Jointly Applied Pruning and Quantization
Automated Model Compression by Jointly Applied Pruning and Quantization
Wenting Tang
Xingxing Wei
Yue Liu
MQ
128
8
0
12 Nov 2020
Softer Pruning, Incremental Regularization
Softer Pruning, Incremental RegularizationInternational Conference on Pattern Recognition (ICPR), 2020
Linhang Cai
Zhulin An
Chuanguang Yang
Yongjun Xu
159
22
0
19 Oct 2020
Structured Convolutions for Efficient Neural Network Design
Structured Convolutions for Efficient Neural Network Design
Brandon Smart
Yizhe Zhang
J. Lin
Fatih Porikli
249
8
0
06 Aug 2020
EDCompress: Energy-Aware Model Compression for Dataflows
EDCompress: Energy-Aware Model Compression for Dataflows
Zhehui Wang
Yaoyu Zhang
Qiufeng Wang
Rick Siow Mong Goh
208
2
0
08 Jun 2020
Edge Intelligence: Architectures, Challenges, and Applications
Edge Intelligence: Architectures, Challenges, and Applications
Dianlei Xu
Tong Li
Yong Li
Xiang Su
Sasu Tarkoma
Tao Jiang
Jon Crowcroft
Pan Hui
289
30
0
26 Mar 2020
Learned Threshold Pruning
Learned Threshold Pruning
K. Azarian
Brandon Smart
Jinwon Lee
Tijmen Blankevoort
MQ
272
40
0
28 Feb 2020
An Adaptive Locally Connected Neuron Model: Focusing Neuron
An Adaptive Locally Connected Neuron Model: Focusing Neuron
F. Boray Tek
245
6
0
31 Aug 2018
Constructing Deep Neural Networks by Bayesian Network Structure Learning
Constructing Deep Neural Networks by Bayesian Network Structure Learning
R. Y. Rohekar
Shami Nisimov
Yaniv Gurwicz
G. Koren
Gal Novik
BDL
390
27
0
24 Jun 2018
Dynamic Graph Convolutional Networks
Dynamic Graph Convolutional Networks
Franco Manessi
A. Rozza
M. Manzo
GNN
269
443
0
20 Apr 2017
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