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Explaining and Harnessing Adversarial Examples
v1v2v3 (latest)

Explaining and Harnessing Adversarial Examples

20 December 2014
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
    AAMLGAN
ArXiv (abs)PDFHTML

Papers citing "Explaining and Harnessing Adversarial Examples"

50 / 8,348 papers shown
Title
Confidence from Invariance to Image Transformations
Confidence from Invariance to Image Transformations
Yuval Bahat
Gregory Shakhnarovich
74
20
0
02 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for
  Regression Learning
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Matthew Jagielski
Alina Oprea
Battista Biggio
Chang-rui Liu
Cristina Nita-Rotaru
Yue Liu
AAML
104
764
0
01 Apr 2018
Adversarial Attacks and Defences Competition
Adversarial Attacks and Defences Competition
Alexey Kurakin
Ian Goodfellow
Samy Bengio
Yinpeng Dong
Fangzhou Liao
...
Junjiajia Long
Yerkebulan Berdibekov
Takuya Akiba
Seiya Tokui
Motoki Abe
AAMLSILM
95
322
0
31 Mar 2018
Learning to Anonymize Faces for Privacy Preserving Action Detection
Learning to Anonymize Faces for Privacy Preserving Action Detection
Zhongzheng Ren
Yong Jae Lee
Michael S. Ryoo
CVBMPICV
151
205
0
30 Mar 2018
Joint Optimization Framework for Learning with Noisy Labels
Joint Optimization Framework for Learning with Noisy Labels
Daiki Tanaka
Daiki Ikami
T. Yamasaki
Kiyoharu Aizawa
NoLa
111
713
0
30 Mar 2018
Security Consideration For Deep Learning-Based Image Forensics
Security Consideration For Deep Learning-Based Image Forensics
Wei Zhao
Pengpeng Yang
R. Ni
Yao-Min Zhao
Haorui Wu
AAML
35
5
0
29 Mar 2018
Defending against Adversarial Images using Basis Functions
  Transformations
Defending against Adversarial Images using Basis Functions Transformations
Uri Shaham
J. Garritano
Yutaro Yamada
Ethan Weinberger
A. Cloninger
Xiuyuan Cheng
Kelly P. Stanton
Y. Kluger
AAML
69
57
0
28 Mar 2018
The Effects of JPEG and JPEG2000 Compression on Attacks using
  Adversarial Examples
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples
Ayse Elvan Aydemir
A. Temi̇zel
T. Taşkaya-Temizel
AAML
59
32
0
28 Mar 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing
  the Subspaces of Adversarial Examples
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples
Pei-Hsuan Lu
Pin-Yu Chen
Chia-Mu Yu
AAML
66
26
0
26 Mar 2018
Clipping free attacks against artificial neural networks
Clipping free attacks against artificial neural networks
B. Addad
Jérôme Kodjabachian
Christophe Meyer
AAML
29
1
0
26 Mar 2018
Generalizability vs. Robustness: Adversarial Examples for Medical
  Imaging
Generalizability vs. Robustness: Adversarial Examples for Medical Imaging
Magdalini Paschali
Sailesh Conjeti
Fernando Navarro
Nassir Navab
OODMedImAAML
97
92
0
23 Mar 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian
  Regularization
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Daniel Jakubovitz
Raja Giryes
AAML
99
210
0
23 Mar 2018
Understanding Measures of Uncertainty for Adversarial Example Detection
Understanding Measures of Uncertainty for Adversarial Example Detection
Lewis Smith
Y. Gal
UQCV
96
365
0
22 Mar 2018
Adversarial Defense based on Structure-to-Signal Autoencoders
Adversarial Defense based on Structure-to-Signal Autoencoders
Joachim Folz
Sebastián M. Palacio
Jörn Hees
Damian Borth
Andreas Dengel
AAML
71
32
0
21 Mar 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Lei Ma
Felix Juefei Xu
Fuyuan Zhang
Jiyuan Sun
Minhui Xue
...
Ting Su
Li Li
Yang Liu
Jianjun Zhao
Yadong Wang
ELM
80
626
0
20 Mar 2018
An Improved Evaluation Framework for Generative Adversarial Networks
An Improved Evaluation Framework for Generative Adversarial Networks
Shaohui Liu
Yi Wei
Jiwen Lu
Jie Zhou
EGVM
59
49
0
20 Mar 2018
Towards Explanation of DNN-based Prediction with Guided Feature
  Inversion
Towards Explanation of DNN-based Prediction with Guided Feature Inversion
Mengnan Du
Ninghao Liu
Qingquan Song
Helen Zhou
FAtt
106
127
0
19 Mar 2018
Improving Transferability of Adversarial Examples with Input Diversity
Improving Transferability of Adversarial Examples with Input Diversity
Cihang Xie
Zhishuai Zhang
Yuyin Zhou
Song Bai
Jianyu Wang
Zhou Ren
Alan Yuille
AAML
119
1,132
0
19 Mar 2018
Technical Report: When Does Machine Learning FAIL? Generalized
  Transferability for Evasion and Poisoning Attacks
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks
Octavian Suciu
R. Marginean
Yigitcan Kaya
Hal Daumé
Tudor Dumitras
AAML
88
287
0
19 Mar 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
70
399
0
17 Mar 2018
Adversarial Logit Pairing
Adversarial Logit Pairing
Harini Kannan
Alexey Kurakin
Ian Goodfellow
AAML
103
629
0
16 Mar 2018
Semantic Adversarial Examples
Semantic Adversarial Examples
Hossein Hosseini
Radha Poovendran
GANAAML
108
199
0
16 Mar 2018
Joint Recognition of Handwritten Text and Named Entities with a Neural
  End-to-end Model
Joint Recognition of Handwritten Text and Named Entities with a Neural End-to-end Model
Manuel Carbonell
M. Villegas
Alicia Fornés
Josep Lladós
55
27
0
16 Mar 2018
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis
  Tool
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool
Feng Liu
Tao Xiang
Timothy M. Hospedales
Wankou Yang
Changyin Sun
71
29
0
16 Mar 2018
Deep Co-Training for Semi-Supervised Image Recognition
Deep Co-Training for Semi-Supervised Image Recognition
Siyuan Qiao
Wei Shen
Zhishuai Zhang
Bo Wang
Alan Yuille
67
455
0
15 Mar 2018
Large Margin Deep Networks for Classification
Large Margin Deep Networks for Classification
Gamaleldin F. Elsayed
Dilip Krishnan
H. Mobahi
Kevin Regan
Samy Bengio
MQ
74
285
0
15 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via
  Collaborative Multi-task Training
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training
Derui Wang
Chaoran Li
S. Wen
Surya Nepal
Yang Xiang
AAML
74
30
0
14 Mar 2018
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial
  Examples
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples
Zihao Liu
Qi Liu
Tao Liu
Nuo Xu
Xue Lin
Yanzhi Wang
Wujie Wen
AAMLMQ
85
265
0
14 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick McDaniel
OODAAML
156
508
0
13 Mar 2018
Invisible Mask: Practical Attacks on Face Recognition with Infrared
Invisible Mask: Practical Attacks on Face Recognition with Infrared
Zhe Zhou
Di Tang
Wenyuan Xu
Weili Han
Xiangyu Liu
Kehuan Zhang
CVBMAAML
68
103
0
13 Mar 2018
Compact Convolutional Neural Networks for Classification of Asynchronous
  Steady-state Visual Evoked Potentials
Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials
Nicholas R. Waytowich
Vernon J. Lawhern
J. Garcia
J. Cummings
J. Faller
P. Sajda
J. Vettel
70
187
0
12 Mar 2018
An Introduction to Image Synthesis with Generative Adversarial Nets
An Introduction to Image Synthesis with Generative Adversarial Nets
He Huang
Philip S. Yu
Changhu Wang
GAN
89
186
0
12 Mar 2018
Deep Dictionary Learning: A PARametric NETwork Approach
Deep Dictionary Learning: A PARametric NETwork Approach
Shahin Mahdizadehaghdam
Ashkan Panahi
Hamid Krim
Liyi Dai
78
64
0
11 Mar 2018
Testing Deep Neural Networks
Testing Deep Neural Networks
Youcheng Sun
Xiaowei Huang
Daniel Kroening
James Sharp
Matthew Hill
Rob Ashmore
AAML
88
219
0
10 Mar 2018
Variance Networks: When Expectation Does Not Meet Your Expectations
Variance Networks: When Expectation Does Not Meet Your Expectations
Kirill Neklyudov
Dmitry Molchanov
Arsenii Ashukha
Dmitry Vetrov
UQCV
94
23
0
10 Mar 2018
Speech Recognition: Keyword Spotting Through Image Recognition
Speech Recognition: Keyword Spotting Through Image Recognition
Sanjay Krishna Gouda
S. Kanetkar
David J. Harrison
Manfred K. Warmuth
56
22
0
10 Mar 2018
Explaining Black-box Android Malware Detection
Explaining Black-box Android Malware Detection
Marco Melis
Davide Maiorca
Battista Biggio
Giorgio Giacinto
Fabio Roli
AAMLFAtt
49
44
0
09 Mar 2018
The Challenge of Crafting Intelligible Intelligence
The Challenge of Crafting Intelligible Intelligence
Daniel S. Weld
Gagan Bansal
58
244
0
09 Mar 2018
Rethinking Feature Distribution for Loss Functions in Image
  Classification
Rethinking Feature Distribution for Loss Functions in Image Classification
Weitao Wan
Yuanyi Zhong
Tianpeng Li
Jiansheng Chen
80
168
0
08 Mar 2018
Sparse Adversarial Perturbations for Videos
Sparse Adversarial Perturbations for Videos
Xingxing Wei
Jun Zhu
Hang Su
AAML
77
145
0
07 Mar 2018
Style Memory: Making a Classifier Network Generative
Style Memory: Making a Classifier Network Generative
R. Wiyatno
Jeff Orchard
70
4
0
05 Mar 2018
Adversarial Extreme Multi-label Classification
Adversarial Extreme Multi-label Classification
Rohit Babbar
Bernhard Schölkopf
60
16
0
05 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense
Stochastic Activation Pruning for Robust Adversarial Defense
Guneet Singh Dhillon
Kamyar Azizzadenesheli
Zachary Chase Lipton
Jeremy Bernstein
Jean Kossaifi
Aran Khanna
Anima Anandkumar
AAML
98
548
0
05 Mar 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
SILMAAML
118
245
0
03 Mar 2018
Protecting JPEG Images Against Adversarial Attacks
Protecting JPEG Images Against Adversarial Attacks
Aaditya (Adi) Prakash
N. Moran
Solomon Garber
Antonella DiLillo
J. Storer
AAML
82
34
0
02 Mar 2018
Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep
  Learning
Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning
Sanjit Bhat
David Lu
Albert Kwon
S. Devadas
AAML
71
195
0
28 Feb 2018
Adversarial Active Learning for Deep Networks: a Margin Based Approach
Adversarial Active Learning for Deep Networks: a Margin Based Approach
Mélanie Ducoffe
F. Precioso
GANAAML
153
278
0
27 Feb 2018
Understanding and Enhancing the Transferability of Adversarial Examples
Understanding and Enhancing the Transferability of Adversarial Examples
Lei Wu
Zhanxing Zhu
Cheng Tai
E. Weinan
AAMLSILM
80
99
0
27 Feb 2018
On the Suitability of $L_p$-norms for Creating and Preventing
  Adversarial Examples
On the Suitability of LpL_pLp​-norms for Creating and Preventing Adversarial Examples
Mahmood Sharif
Lujo Bauer
Michael K. Reiter
AAML
144
138
0
27 Feb 2018
Retrieval-Augmented Convolutional Neural Networks for Improved
  Robustness against Adversarial Examples
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples
Jake Zhao
Kyunghyun Cho
AAML
160
20
0
26 Feb 2018
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