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ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
v1v2 (latest)

ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks

12 May 2025
Wenhao Hu
Paul Henderson
José Cano
ArXiv (abs)PDFHTML

Papers citing "ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks"

27 / 27 papers shown
Title
Local Masking Meets Progressive Freezing: Crafting Efficient Vision
  Transformers for Self-Supervised Learning
Local Masking Meets Progressive Freezing: Crafting Efficient Vision Transformers for Self-Supervised Learning
Utku Mert Topcuoglu
Erdem Akagündüz
72
1
0
02 Dec 2023
A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models
A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models
Junjie Ye
Xuanting Chen
Nuo Xu
Can Zu
Zekai Shao
...
Jie Zhou
Siming Chen
Tao Gui
Qi Zhang
Xuanjing Huang
ELM
59
331
0
18 Mar 2023
Automatic Attention Pruning: Improving and Automating Model Pruning
  using Attentions
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
Kaiqi Zhao
Animesh Jain
Ming Zhao
49
11
0
14 Mar 2023
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based
  Networks
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks
Shiyu Liu
Chong Min John Tan
Mehul Motani
CLL
51
4
0
17 Oct 2021
AutoFreeze: Automatically Freezing Model Blocks to Accelerate
  Fine-tuning
AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning
Yuhan Liu
Saurabh Agarwal
Shivaram Venkataraman
OffRL
48
56
0
02 Feb 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
314
723
0
31 Jan 2021
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
267
1,052
0
06 Mar 2020
Pruning Filters while Training for Efficiently Optimizing Deep Learning
  Networks
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks
Sourjya Roy
Priyadarshini Panda
G. Srinivasan
A. Raghunathan
3DPCVLM
64
19
0
05 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
520
42,559
0
03 Dec 2019
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning
Jaejun Lee
Raphael Tang
Jimmy J. Lin
67
126
0
08 Nov 2019
On the Variance of the Adaptive Learning Rate and Beyond
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
Jiawei Han
ODL
287
1,906
0
08 Aug 2019
Optuna: A Next-generation Hyperparameter Optimization Framework
Optuna: A Next-generation Hyperparameter Optimization Framework
Takuya Akiba
Shotaro Sano
Toshihiko Yanase
Takeru Ohta
Masanori Koyama
663
5,808
0
25 Jul 2019
Towards Explaining the Regularization Effect of Initial Large Learning
  Rate in Training Neural Networks
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
Yuanzhi Li
Colin Wei
Tengyu Ma
53
299
0
10 Jul 2019
Are Sixteen Heads Really Better than One?
Are Sixteen Heads Really Better than One?
Paul Michel
Omer Levy
Graham Neubig
MoE
103
1,062
0
25 May 2019
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks
Yang He
Guoliang Kang
Xuanyi Dong
Yanwei Fu
Yi Yang
AAMLVLM
66
965
0
21 Aug 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle
Michael Carbin
242
3,484
0
09 Mar 2018
Visualizing the Loss Landscape of Neural Nets
Visualizing the Loss Landscape of Neural Nets
Hao Li
Zheng Xu
Gavin Taylor
Christoph Studer
Tom Goldstein
254
1,896
0
28 Dec 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network
  Compression
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
Jian-Hao Luo
Jianxin Wu
Weiyao Lin
58
1,760
0
20 Jul 2017
An Entropy-based Pruning Method for CNN Compression
An Entropy-based Pruning Method for CNN Compression
Jian-Hao Luo
Jianxin Wu
37
180
0
19 Jun 2017
FreezeOut: Accelerate Training by Progressively Freezing Layers
FreezeOut: Accelerate Training by Progressively Freezing Layers
Andrew Brock
Theodore Lim
J. Ritchie
Nick Weston
47
125
0
15 Jun 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.2K
20,858
0
17 Apr 2017
An overview of gradient descent optimization algorithms
An overview of gradient descent optimization algorithms
Sebastian Ruder
ODL
204
6,199
0
15 Sep 2016
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
195
3,697
0
31 Aug 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
775
36,861
0
25 Aug 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
349
7,995
0
23 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
362
19,660
0
09 Mar 2015
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