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Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

28 August 2023
Samuel Horváth
Stefanos Laskaridis
Shashank Rajput
Hongyi Wang
    BDL
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Papers citing "Maestro: Uncovering Low-Rank Structures via Trainable Decomposition"

5 / 55 papers shown
Title
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
255
8,833
0
01 Oct 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
323
18,613
0
06 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,348
0
04 Sep 2014
Speeding up Convolutional Neural Networks with Low Rank Expansions
Speeding up Convolutional Neural Networks with Low Rank Expansions
Max Jaderberg
Andrea Vedaldi
Andrew Zisserman
128
1,463
0
15 May 2014
Learning Ordered Representations with Nested Dropout
Learning Ordered Representations with Nested Dropout
Oren Rippel
M. Gelbart
Ryan P. Adams
SSL
103
89
0
05 Feb 2014
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