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DECORE: Deep Compression with Reinforcement Learning

DECORE: Deep Compression with Reinforcement Learning

11 June 2021
Manoj Alwani
Yang Wang
Vashisht Madhavan
    AI4CE
ArXivPDFHTML

Papers citing "DECORE: Deep Compression with Reinforcement Learning"

19 / 19 papers shown
Title
Hardware-Aware DNN Compression for Homogeneous Edge Devices
Kunlong Zhang
Guiying Li
Ning Lu
Peng Yang
K. Tang
73
0
0
28 Jan 2025
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
M. Deutel
G. Kontes
Christopher Mutschler
Jürgen Teich
114
0
0
23 May 2023
An Information Theory-inspired Strategy for Automatic Network Pruning
An Information Theory-inspired Strategy for Automatic Network Pruning
Xiawu Zheng
Yuexiao Ma
Teng Xi
Gang Zhang
Errui Ding
Yuchao Li
Jie Chen
Yonghong Tian
Rongrong Ji
81
13
0
19 Aug 2021
Neuroevolution in Deep Neural Networks: Current Trends and Future
  Challenges
Neuroevolution in Deep Neural Networks: Current Trends and Future Challenges
E. Galván
P. Mooney
47
130
0
09 Jun 2020
Learning in the Frequency Domain
Learning in the Frequency Domain
Kai Xu
Minghai Qin
Fei Sun
Yuhao Wang
Yen-kuang Chen
Fengbo Ren
66
400
0
27 Feb 2020
HRank: Filter Pruning using High-Rank Feature Map
HRank: Filter Pruning using High-Rank Feature Map
Mingbao Lin
Rongrong Ji
Yan Wang
Yichen Zhang
Baochang Zhang
Yonghong Tian
Ling Shao
41
719
0
24 Feb 2020
DARTS: Differentiable Architecture Search
DARTS: Differentiable Architecture Search
Hanxiao Liu
Karen Simonyan
Yiming Yang
140
4,326
0
24 Jun 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Yihui He
Ji Lin
Zhijian Liu
Hanrui Wang
Li Li
Song Han
57
1,346
0
10 Feb 2018
Quantization and Training of Neural Networks for Efficient
  Integer-Arithmetic-Only Inference
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Benoit Jacob
S. Kligys
Bo Chen
Menglong Zhu
Matthew Tang
Andrew G. Howard
Hartwig Adam
Dmitry Kalenichenko
MQ
110
3,090
0
15 Dec 2017
Learning Efficient Convolutional Networks through Network Slimming
Learning Efficient Convolutional Networks through Network Slimming
Zhuang Liu
Jianguo Li
Zhiqiang Shen
Gao Huang
Shoumeng Yan
Changshui Zhang
89
2,407
0
22 Aug 2017
Channel Pruning for Accelerating Very Deep Neural Networks
Channel Pruning for Accelerating Very Deep Neural Networks
Yihui He
Xiangyu Zhang
Jian Sun
182
2,513
0
19 Jul 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
142
3,676
0
31 Aug 2016
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNN
AI4CE
237
18,300
0
27 May 2016
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural
  Networks
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Mohammad Rastegari
Vicente Ordonez
Joseph Redmon
Ali Farhadi
MQ
120
4,342
0
16 Mar 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB
  model size
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
100
7,448
0
24 Feb 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
142
8,805
0
04 Feb 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
154
8,793
0
01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks
Learning both Weights and Connections for Efficient Neural Networks
Song Han
Jeff Pool
J. Tran
W. Dally
CVBM
157
6,628
0
08 Jun 2015
Exploiting Linear Structure Within Convolutional Networks for Efficient
  Evaluation
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
Emily L. Denton
Wojciech Zaremba
Joan Bruna
Yann LeCun
Rob Fergus
FAtt
74
1,682
0
02 Apr 2014
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