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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 / 8,334 papers shown
Title
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
Basel Alomair
AAML
209
1,744
0
08 Nov 2016
Semi-supervised deep learning by metric embedding
Semi-supervised deep learning by metric embedding
Elad Hoffer
Nir Ailon
SSL
75
27
0
04 Nov 2016
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
491
3,152
0
04 Nov 2016
Towards Lifelong Self-Supervision: A Deep Learning Direction for
  Robotics
Towards Lifelong Self-Supervision: A Deep Learning Direction for Robotics
J. M. Wong
79
11
0
01 Nov 2016
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
284
2,534
0
26 Oct 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
290
945
0
21 Oct 2016
Learning to Protect Communications with Adversarial Neural Cryptography
Learning to Protect Communications with Adversarial Neural Cryptography
Martín Abadi
David G. Andersen
FedMLGAN
95
213
0
21 Oct 2016
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of
  Convolutional Neural Networks Approaches
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
E. Rodner
Marcel Simon
Robert B. Fisher
Joachim Denzler
73
40
0
21 Oct 2016
Digital Makeup from Internet Images
Digital Makeup from Internet Images
Asad Khan
Muhammad Ahmad
Yudong Guo
Ligang Liu
DiffM
32
2
0
16 Oct 2016
Are Accuracy and Robustness Correlated?
Are Accuracy and Robustness Correlated?
Andras Rozsa
Manuel Günther
Terrance E. Boult
AAML
78
61
0
14 Oct 2016
Assessing Threat of Adversarial Examples on Deep Neural Networks
Assessing Threat of Adversarial Examples on Deep Neural Networks
Abigail Graese
Andras Rozsa
Terrance E. Boult
AAML
79
57
0
13 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
603
20,227
0
07 Oct 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
228
3,488
0
07 Oct 2016
DeepDGA: Adversarially-Tuned Domain Generation and Detection
DeepDGA: Adversarially-Tuned Domain Generation and Detection
Hyrum S. Anderson
Jonathan Woodbridge
Bobby Filar
AAML
99
203
0
06 Oct 2016
Supervision via Competition: Robot Adversaries for Learning Tasks
Supervision via Competition: Robot Adversaries for Learning Tasks
Lerrel Pinto
James Davidson
Abhinav Gupta
SSL
94
82
0
05 Oct 2016
Adversary Resistant Deep Neural Networks with an Application to Malware
  Detection
Adversary Resistant Deep Neural Networks with an Application to Malware Detection
Qinglong Wang
Wenbo Guo
Kaixuan Zhang
Alexander Ororbia
Masashi Sugiyama
C. Lee Giles
Xue Liu
AAML
102
175
0
05 Oct 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
Nicolas Papernot
Fartash Faghri
Nicholas Carlini
Ian Goodfellow
Reuben Feinman
...
David Berthelot
P. Hendricks
Jonas Rauber
Rujun Long
Patrick McDaniel
AAML
98
516
0
03 Oct 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
559
2,947
0
15 Sep 2016
Fitted Learning: Models with Awareness of their Limits
Fitted Learning: Models with Awareness of their Limits
Navid Kardan
Kenneth O. Stanley
CLL
79
16
0
07 Sep 2016
Direct Feedback Alignment Provides Learning in Deep Neural Networks
Direct Feedback Alignment Provides Learning in Deep Neural Networks
Arild Nøkland
ODL
206
462
0
06 Sep 2016
Robustness of classifiers: from adversarial to random noise
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
110
376
0
31 Aug 2016
A Boundary Tilting Persepective on the Phenomenon of Adversarial
  Examples
A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples
T. Tanay
Lewis D. Griffin
AAML
103
272
0
27 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
290
8,604
0
16 Aug 2016
A study of the effect of JPG compression on adversarial images
A study of the effect of JPG compression on adversarial images
Gintare Karolina Dziugaite
Zoubin Ghahramani
Daniel M. Roy
AAML
96
536
0
02 Aug 2016
Early Methods for Detecting Adversarial Images
Early Methods for Detecting Adversarial Images
Dan Hendrycks
Kevin Gimpel
AAML
105
236
0
01 Aug 2016
Unsupervised Learning from Continuous Video in a Scalable Predictive
  Recurrent Network
Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
Filip Piekniewski
Patryk A. Laurent
Csaba Petre
Micah Richert
Dimitry Fisher
Todd Hylton
56
17
0
22 Jul 2016
On the Effectiveness of Defensive Distillation
On the Effectiveness of Defensive Distillation
Nicolas Papernot
Patrick McDaniel
AAML
64
65
0
18 Jul 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
600
5,922
0
08 Jul 2016
Towards Verified Artificial Intelligence
Towards Verified Artificial Intelligence
Sanjit A. Seshia
Dorsa Sadigh
S. Shankar Sastry
128
203
0
27 Jun 2016
Concrete Problems in AI Safety
Concrete Problems in AI Safety
Dario Amodei
C. Olah
Jacob Steinhardt
Paul Christiano
John Schulman
Dandelion Mané
312
2,406
0
21 Jun 2016
On the Expressive Power of Deep Neural Networks
On the Expressive Power of Deep Neural Networks
M. Raghu
Ben Poole
Jon M. Kleinberg
Surya Ganguli
Jascha Narain Sohl-Dickstein
106
791
0
16 Jun 2016
Adversarial Perturbations Against Deep Neural Networks for Malware
  Classification
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse
Nicolas Papernot
Praveen Manoharan
Michael Backes
Patrick McDaniel
AAML
106
419
0
14 Jun 2016
Dense Associative Memory for Pattern Recognition
Dense Associative Memory for Pattern Recognition
Dmitry Krotov
J. Hopfield
120
348
0
03 Jun 2016
Deep convolutional neural networks for predominant instrument
  recognition in polyphonic music
Deep convolutional neural networks for predominant instrument recognition in polyphonic music
Yoonchang Han
Jae‐Hun Kim
Kyogu Lee
82
207
0
31 May 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
SILMAAML
119
1,744
0
24 May 2016
Measuring Neural Net Robustness with Constraints
Measuring Neural Net Robustness with Constraints
Osbert Bastani
Yani Andrew Ioannou
Leonidas Lampropoulos
Dimitrios Vytiniotis
A. Nori
A. Criminisi
AAML
106
424
0
24 May 2016
Adversarial Diversity and Hard Positive Generation
Adversarial Diversity and Hard Positive Generation
Andras Rozsa
Ethan M. Rudd
Terrance E. Boult
112
257
0
05 May 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Nicolas Papernot
Patrick McDaniel
A. Swami
Richard E. Harang
AAMLGANSILM
81
457
0
28 Apr 2016
Makeup like a superstar: Deep Localized Makeup Transfer Network
Makeup like a superstar: Deep Localized Makeup Transfer Network
Si Liu
Xinyu Ou
Ruihe Qian
Wei Wang
Xiaochun Cao
OOD
86
89
0
25 Apr 2016
Humans and deep networks largely agree on which kinds of variation make
  object recognition harder
Humans and deep networks largely agree on which kinds of variation make object recognition harder
Saeed Reza Kheradpisheh
M. Ghodrati
M. Ganjtabesh
T. Masquelier
OOD
60
34
0
21 Apr 2016
Improving the Robustness of Deep Neural Networks via Stability Training
Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng
Yang Song
Thomas Leung
Ian Goodfellow
OOD
58
639
0
15 Apr 2016
Understanding How Image Quality Affects Deep Neural Networks
Understanding How Image Quality Affects Deep Neural Networks
Samuel F. Dodge
Lina Karam
VLM
89
732
0
14 Apr 2016
A General Retraining Framework for Scalable Adversarial Classification
A General Retraining Framework for Scalable Adversarial Classification
Bo Li
Yevgeniy Vorobeychik
Xinyun Chen
AAML
69
32
0
09 Apr 2016
Reasoning About Pragmatics with Neural Listeners and Speakers
Reasoning About Pragmatics with Neural Listeners and Speakers
Jacob Andreas
Dan Klein
ReLMLRM
111
175
0
02 Apr 2016
Evolution of active categorical image classification via saccadic eye
  movement
Evolution of active categorical image classification via saccadic eye movement
Randal S. Olson
J. Moore
C. Adami
42
4
0
27 Mar 2016
A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic
  Extraction of Semantics, Formation of Integrated Concepts and Re-selection
  Features for Ambiguity
A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity
Peijie Yin
Hong Qiao
Wei Wu
Lu Qi
Yinlin Li
Shanlin Zhong
Bo Zhang
21
8
0
25 Mar 2016
Deep Learning in Bioinformatics
Deep Learning in Bioinformatics
Seonwoo Min
Byunghan Lee
Sungroh Yoon
AI4CE3DV
112
1,364
0
21 Mar 2016
A Survey of Stealth Malware: Attacks, Mitigation Measures, and Steps
  Toward Autonomous Open World Solutions
A Survey of Stealth Malware: Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions
Ethan M. Rudd
Andras Rozsa
Manuel Günther
Terrance E. Boult
93
156
0
19 Mar 2016
Suppressing the Unusual: towards Robust CNNs using Symmetric Activation
  Functions
Suppressing the Unusual: towards Robust CNNs using Symmetric Activation Functions
Qiyang Zhao
Lewis D. Griffin
AAML
71
28
0
16 Mar 2016
Multifaceted Feature Visualization: Uncovering the Different Types of
  Features Learned By Each Neuron in Deep Neural Networks
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks
Anh Totti Nguyen
J. Yosinski
Jeff Clune
117
330
0
11 Feb 2016
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