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Parametric Noise Injection: Trainable Randomness to Improve Deep Neural
  Network Robustness against Adversarial Attack

Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack

22 November 2018
Adnan Siraj Rakin
Zhezhi He
Deliang Fan
    AAML
ArXivPDFHTML

Papers citing "Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack"

42 / 42 papers shown
Title
Exploring Channel Distinguishability in Local Neighborhoods of the Model Space in Quantum Neural Networks
Exploring Channel Distinguishability in Local Neighborhoods of the Model Space in Quantum Neural Networks
Sabrina Herbst
S. S. Cranganore
Vincenzo De Maio
Ivona Brandić
59
0
0
17 Feb 2025
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective
Xueqiong Yuan
Jipeng Li
E. Kuruoglu
UQCV
BDL
56
0
0
21 Jan 2025
Personality Alignment of Large Language Models
Personality Alignment of Large Language Models
Minjun Zhu
Linyi Yang
Yue Zhang
Yue Zhang
ALM
78
6
0
21 Aug 2024
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
Yonggan Fu
Yang Zhao
Qixuan Yu
Chaojian Li
Yingyan Lin
AAML
59
12
0
11 Sep 2021
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural
  Network
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu
Yao Li
Chongruo Wu
Cho-Jui Hsieh
AAML
OOD
39
171
0
01 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks
A Kernel Perspective for Regularizing Deep Neural Networks
A. Bietti
Grégoire Mialon
Dexiong Chen
Julien Mairal
46
15
0
30 Sep 2018
Defending Against Adversarial Attacks by Leveraging an Entire GAN
Defending Against Adversarial Attacks by Leveraging an Entire GAN
G. Santhanam
Paulina Grnarova
AAML
23
40
0
27 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using
  Generative Models
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei
Maya Kabkab
Rama Chellappa
AAML
GAN
61
1,172
0
17 May 2018
On the Robustness of the CVPR 2018 White-Box Adversarial Example
  Defenses
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
Anish Athalye
Nicholas Carlini
AAML
27
169
0
10 Apr 2018
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with
  Adversarial Examples
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples
Minhao Cheng
Jinfeng Yi
Pin-Yu Chen
Huan Zhang
Cho-Jui Hsieh
SILM
AAML
65
243
0
03 Mar 2018
L2-Nonexpansive Neural Networks
L2-Nonexpansive Neural Networks
Haifeng Qian
M. Wegman
32
74
0
22 Feb 2018
Identify Susceptible Locations in Medical Records via Adversarial
  Attacks on Deep Predictive Models
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
Mengying Sun
Fengyi Tang
Jinfeng Yi
Fei Wang
Jiayu Zhou
AAML
OOD
MedIm
45
62
0
13 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy
Certified Robustness to Adversarial Examples with Differential Privacy
Mathias Lécuyer
Vaggelis Atlidakis
Roxana Geambasu
Daniel J. Hsu
Suman Jana
SILM
AAML
69
931
0
09 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
145
3,171
0
01 Feb 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini
D. Wagner
AAML
53
1,076
0
05 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Ajmal Mian
AAML
51
1,862
0
02 Jan 2018
Attacking Visual Language Grounding with Adversarial Examples: A Case
  Study on Neural Image Captioning
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Hongge Chen
Huan Zhang
Pin-Yu Chen
Jinfeng Yi
Cho-Jui Hsieh
GAN
AAML
44
49
0
06 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble
Towards Robust Neural Networks via Random Self-ensemble
Xuanqing Liu
Minhao Cheng
Huan Zhang
Cho-Jui Hsieh
FedML
AAML
76
419
0
02 Dec 2017
Mitigating Adversarial Effects Through Randomization
Mitigating Adversarial Effects Through Randomization
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Zhou Ren
Alan Yuille
AAML
72
1,050
0
06 Nov 2017
Fooling Vision and Language Models Despite Localization and Attention
  Mechanism
Fooling Vision and Language Models Despite Localization and Attention Mechanism
Xiaojun Xu
Xinyun Chen
Chang-rui Liu
Anna Rohrbach
Trevor Darrell
D. Song
AAML
42
41
0
25 Sep 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural
  Networks without Training Substitute Models
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
Pin-Yu Chen
Huan Zhang
Yash Sharma
Jinfeng Yi
Cho-Jui Hsieh
AAML
43
1,864
0
14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
181
11,962
0
19 Jun 2017
Spectral Norm Regularization for Improving the Generalizability of Deep
  Learning
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida
Takeru Miyato
64
328
0
31 May 2017
Delving into adversarial attacks on deep policies
Delving into adversarial attacks on deep policies
Jernej Kos
D. Song
AAML
34
224
0
18 May 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation
Universal Adversarial Perturbations Against Semantic Image Segmentation
J. H. Metzen
Mummadi Chaithanya Kumar
Thomas Brox
Volker Fischer
AAML
111
287
0
19 Apr 2017
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
D. Song
AAML
105
1,727
0
08 Nov 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
146
8,497
0
16 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
480
5,868
0
08 Jul 2016
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low
  Bitwidth Gradients
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
Shuchang Zhou
Yuxin Wu
Zekun Ni
Xinyu Zhou
He Wen
Yuheng Zou
MQ
87
2,080
0
20 Jun 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks
  using Adversarial Samples
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
SILM
AAML
70
1,735
0
24 May 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAU
AAML
30
3,656
0
08 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
998
192,638
0
10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
47
3,947
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
87
4,878
0
14 Nov 2015
BinaryConnect: Training Deep Neural Networks with binary weights during
  propagations
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux
Yoshua Bengio
J. David
MQ
100
2,976
0
02 Nov 2015
DeepDriving: Learning Affordance for Direct Perception in Autonomous
  Driving
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
Chenyi Chen
Ari Seff
A. Kornhauser
Jianxiong Xiao
62
1,757
0
01 May 2015
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
210
43,154
0
11 Feb 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
95
18,534
0
06 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
421
149,474
0
22 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
122
18,922
0
20 Dec 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
308
27,205
0
01 Sep 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
101
14,831
1
21 Dec 2013
1