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Concurrent Training and Layer Pruning of Deep Neural Networks

Concurrent Training and Layer Pruning of Deep Neural Networks

6 June 2024
Valentin Frank Ingmar Guenter
Athanasios Sideris
    3DPC
ArXivPDFHTML

Papers citing "Concurrent Training and Layer Pruning of Deep Neural Networks"

6 / 6 papers shown
Title
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning
Yupei Li
M. Milling
Björn Schuller
AI4CE
107
0
0
27 Mar 2025
Reassessing Layer Pruning in LLMs: New Insights and Methods
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu
Hao Cheng
Yujie Fang
Zeyu Wang
Jiaheng Wei
Dongwei Xu
Qi Xuan
Xiaoniu Yang
Zhaowei Zhu
63
0
0
23 Nov 2024
Complexity-Aware Training of Deep Neural Networks for Optimal Structure
  Discovery
Complexity-Aware Training of Deep Neural Networks for Optimal Structure Discovery
Valentin Frank Ingmar Guenter
Athanasios Sideris
CVBM
18
0
0
14 Nov 2024
SCOP: Scientific Control for Reliable Neural Network Pruning
SCOP: Scientific Control for Reliable Neural Network Pruning
Yehui Tang
Yunhe Wang
Yixing Xu
Dacheng Tao
Chunjing Xu
Chao Xu
Chang Xu
AAML
44
166
0
21 Oct 2020
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
188
1,027
0
06 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
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