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Low-rank Tensor Decomposition for Compression of Convolutional Neural
  Networks Using Funnel Regularization

Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization

7 December 2021
Bo-Shiuan Chu
Che-Rung Lee
ArXivPDFHTML

Papers citing "Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization"

5 / 5 papers shown
Title
Convolutional Neural Network Compression via Dynamic Parameter Rank
  Pruning
Convolutional Neural Network Compression via Dynamic Parameter Rank Pruning
Manish Sharma
Jamison Heard
Eli Saber
Panos P. Markopoulos
20
1
0
15 Jan 2024
Towards Higher Ranks via Adversarial Weight Pruning
Towards Higher Ranks via Adversarial Weight Pruning
Yuchuan Tian
Hanting Chen
Tianyu Guo
Chao Xu
Yunhe Wang
19
2
0
29 Nov 2023
Forward and Inverse Approximation Theory for Linear Temporal
  Convolutional Networks
Forward and Inverse Approximation Theory for Linear Temporal Convolutional Networks
Hao Jiang
Qianxiao Li
AI4TS
10
0
0
29 May 2023
How Informative is the Approximation Error from Tensor Decomposition for
  Neural Network Compression?
How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?
Jetze T. Schuurmans
Kim Batselier
Julian F. P. Kooij
14
1
0
09 May 2023
Position: Tensor Networks are a Valuable Asset for Green AI
Position: Tensor Networks are a Valuable Asset for Green AI
Eva Memmel
Clara Menzen
Jetze T. Schuurmans
Frederiek Wesel
Kim Batselier
25
5
0
25 May 2022
1