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Can pruning improve certified robustness of neural networks?

Can pruning improve certified robustness of neural networks?

15 June 2022
Zhangheng Li
Tianlong Chen
Linyi Li
Yue Liu
Zhangyang Wang
    AAML
ArXivPDFHTML

Papers citing "Can pruning improve certified robustness of neural networks?"

38 / 38 papers shown
Title
ScaleCert: Scalable Certified Defense against Adversarial Patches with
  Sparse Superficial Layers
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Husheng Han
Kaidi Xu
Xing Hu
Xiaobing Chen
Ling Liang
Zidong Du
Qi Guo
Yanzhi Wang
Yunji Chen
AAML
39
20
0
27 Oct 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
Yonggan Fu
Qixuan Yu
Yang Zhang
Shan-Hung Wu
Ouyang Xu
David D. Cox
Yingyan Lin
AAML
OOD
74
30
0
26 Oct 2021
The Second International Verification of Neural Networks Competition
  (VNN-COMP 2021): Summary and Results
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results
Stanley Bak
Changliu Liu
Taylor T. Johnson
NAI
73
112
0
31 Aug 2021
On the Effect of Pruning on Adversarial Robustness
On the Effect of Pruning on Adversarial Robustness
Artur Jordão
Hélio Pedrini
AAML
68
22
0
10 Aug 2021
Fast Certified Robust Training with Short Warmup
Fast Certified Robust Training with Short Warmup
Zhouxing Shi
Yihan Wang
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
AAML
49
56
0
31 Mar 2021
Fast and Complete: Enabling Complete Neural Network Verification with
  Rapid and Massively Parallel Incomplete Verifiers
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu
Huan Zhang
Shiqi Wang
Yihan Wang
Suman Jana
Xue Lin
Cho-Jui Hsieh
79
183
0
27 Nov 2020
Understanding and Improving Fast Adversarial Training
Understanding and Improving Fast Adversarial Training
Maksym Andriushchenko
Nicolas Flammarion
AAML
71
289
0
06 Jul 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron
  Relaxations for Neural Network Verification
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
Christian Tjandraatmadja
Ross Anderson
Joey Huchette
Will Ma
Krunal Patel
J. Vielma
AAML
94
89
0
24 Jun 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
3DPC
VLM
56
19
0
05 Mar 2020
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by
  Enabling Input-Adaptive Inference
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference
Ting-Kuei Hu
Tianlong Chen
Haotao Wang
Zhangyang Wang
OOD
AAML
3DH
48
84
0
24 Feb 2020
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for
  Real-time Execution on Mobile Devices
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices
Xiaolong Ma
Fu-Ming Guo
Wei Niu
Xue Lin
Jian Tang
Kaisheng Ma
Bin Ren
Yanzhi Wang
CVBM
49
176
0
06 Sep 2019
Adversarial Robustness vs Model Compression, or Both?
Adversarial Robustness vs Model Compression, or Both?
Shaokai Ye
Kaidi Xu
Sijia Liu
Jan-Henrik Lambrechts
Huan Zhang
Aojun Zhou
Kaisheng Ma
Yanzhi Wang
Xue Lin
AAML
52
165
0
29 Mar 2019
A Convex Relaxation Barrier to Tight Robustness Verification of Neural
  Networks
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Hadi Salman
Greg Yang
Huan Zhang
Cho-Jui Hsieh
Pengchuan Zhang
AAML
96
269
0
23 Feb 2019
Model Compression with Adversarial Robustness: A Unified Optimization
  Framework
Model Compression with Adversarial Robustness: A Unified Optimization Framework
Shupeng Gui
Haotao Wang
Chen Yu
Haichuan Yang
Zhangyang Wang
Ji Liu
MQ
47
138
0
10 Feb 2019
Are All Layers Created Equal?
Are All Layers Created Equal?
Chiyuan Zhang
Samy Bengio
Y. Singer
58
140
0
06 Feb 2019
Efficient Neural Network Robustness Certification with General
  Activation Functions
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang
Tsui-Wei Weng
Pin-Yu Chen
Cho-Jui Hsieh
Luca Daniel
AAML
89
760
0
02 Nov 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity
SNIP: Single-shot Network Pruning based on Connection Sensitivity
Namhoon Lee
Thalaiyasingam Ajanthan
Philip Torr
VLM
249
1,198
0
04 Oct 2018
Training for Faster Adversarial Robustness Verification via Inducing
  ReLU Stability
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Kai Y. Xiao
Vincent Tjeng
Nur Muhammad (Mahi) Shafiullah
Aleksander Madry
AAML
OOD
41
200
0
09 Sep 2018
Detecting Dead Weights and Units in Neural Networks
Detecting Dead Weights and Units in Neural Networks
Utku Evci
CVBM
56
8
0
15 Jun 2018
Scaling provable adversarial defenses
Scaling provable adversarial defenses
Eric Wong
Frank R. Schmidt
J. H. Metzen
J. Zico Kolter
AAML
76
448
0
31 May 2018
Towards Fast Computation of Certified Robustness for ReLU Networks
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng
Huan Zhang
Hongge Chen
Zhao Song
Cho-Jui Hsieh
Duane S. Boning
Inderjit S. Dhillon
Luca Daniel
AAML
100
694
0
25 Apr 2018
A Systematic DNN Weight Pruning Framework using Alternating Direction
  Method of Multipliers
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
Tianyun Zhang
Shaokai Ye
Kaiqi Zhang
Jian Tang
Wujie Wen
M. Fardad
Yanzhi Wang
57
438
0
10 Apr 2018
A Dual Approach to Scalable Verification of Deep Networks
A Dual Approach to Scalable Verification of Deep Networks
Krishnamurthy Dvijotham
Dvijotham
Robert Stanforth
Sven Gowal
Timothy A. Mann
Pushmeet Kohli
52
399
0
17 Mar 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle
Michael Carbin
225
3,461
0
09 Mar 2018
Certified Defenses against Adversarial Examples
Certified Defenses against Adversarial Examples
Aditi Raghunathan
Jacob Steinhardt
Percy Liang
AAML
105
968
0
29 Jan 2018
SkipNet: Learning Dynamic Routing in Convolutional Networks
SkipNet: Learning Dynamic Routing in Convolutional Networks
Xin Wang
Feng Yu
Zi-Yi Dou
Trevor Darrell
Joseph E. Gonzalez
99
635
0
26 Nov 2017
BlockDrop: Dynamic Inference Paths in Residual Networks
BlockDrop: Dynamic Inference Paths in Residual Networks
Zuxuan Wu
Tushar Nagarajan
Abhishek Kumar
Steven J. Rennie
L. Davis
Kristen Grauman
Rogerio Feris
87
466
0
22 Nov 2017
Provable defenses against adversarial examples via the convex outer
  adversarial polytope
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong
J. Zico Kolter
AAML
123
1,501
0
02 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
278
8,878
0
25 Aug 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
122
2,419
0
22 Aug 2017
A Downsampled Variant of ImageNet as an Alternative to the CIFAR
  datasets
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets
P. Chrabaszcz
I. Loshchilov
Frank Hutter
SSeg
OOD
152
646
0
27 Jul 2017
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
Rüdiger Ehlers
102
626
0
03 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
315
1,867
0
03 Feb 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
190
3,695
0
31 Aug 2016
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
460
43,277
0
11 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
271
19,045
0
20 Dec 2014
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
239
8,401
0
28 Nov 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
268
14,912
1
21 Dec 2013
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