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1412.6572
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Explaining and Harnessing Adversarial Examples
20 December 2014
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
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Papers citing
"Explaining and Harnessing Adversarial Examples"
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Title
Physical Adversarial Examples for Object Detectors
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Florian Tramèr
Atul Prakash
Tadayoshi Kohno
Basel Alomair
AAML
107
473
0
20 Jul 2018
Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding
Tong Chen
Wenjia Niu
Yingxiao Xiang
XiaoXuan Bai
Jiqiang Liu
Zhen Han
Gang Li
AAML
62
23
0
18 Jul 2018
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer
Ryan P. Adams
Ian Goodfellow
David G. Andersen
George E. Dahl
AAML
107
229
0
18 Jul 2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions
Adnan Siraj Rakin
Jinfeng Yi
Boqing Gong
Deliang Fan
AAML
MQ
80
50
0
18 Jul 2018
Online Robust Policy Learning in the Presence of Unknown Adversaries
Aaron J. Havens
Zhanhong Jiang
Soumik Sarkar
AAML
115
44
0
16 Jul 2018
Manifold Adversarial Learning
Shufei Zhang
Kaizhu Huang
Jianke Zhu
Yang Liu
OOD
AAML
59
5
0
16 Jul 2018
NEUZZ: Efficient Fuzzing with Neural Program Smoothing
Dongdong She
Kexin Pei
Dave Epstein
Junfeng Yang
Baishakhi Ray
Suman Jana
81
186
0
15 Jul 2018
Deep Learning in the Wild
Thilo Stadelmann
Mohammadreza Amirian
Ismail Arabaci
M. Arnold
G. Duivesteijn
...
Melanie Geiger
Stefan Lörwald
B. Meier
Katharina Rombach
Lukas Tuggener
67
42
0
13 Jul 2018
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach
Minhao Cheng
Thong Le
Pin-Yu Chen
Jinfeng Yi
Huan Zhang
Cho-Jui Hsieh
AAML
112
348
0
12 Jul 2018
With Friends Like These, Who Needs Adversaries?
Saumya Jetley
Nicholas A. Lord
Philip Torr
AAML
116
70
0
11 Jul 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
201
2,078
0
10 Jul 2018
Attack and defence in cellular decision-making: lessons from machine learning
Thomas J. Rademaker
Emmanuel Bengio
P. Franccois
AAML
51
4
0
10 Jul 2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees
Min Wu
Matthew Wicker
Wenjie Ruan
Xiaowei Huang
Marta Kwiatkowska
AAML
91
111
0
10 Jul 2018
Adaptive Adversarial Attack on Scene Text Recognition
Xiaoyong Yuan
Pan He
Xiaolin Li
Dapeng Oliver Wu
AAML
73
23
0
09 Jul 2018
Efficient ConvNets for Analog Arrays
Malte J. Rasch
Tayfun Gokmen
Mattia Rigotti
W. Haensch
59
11
0
03 Jul 2018
Local Gradients Smoothing: Defense against localized adversarial attacks
Muzammal Naseer
Salman H. Khan
Fatih Porikli
AAML
106
162
0
03 Jul 2018
Adversarial Robustness Toolbox v1.0.0
Maria-Irina Nicolae
M. Sinn
Minh-Ngoc Tran
Beat Buesser
Ambrish Rawat
...
Nathalie Baracaldo
Bryant Chen
Heiko Ludwig
Ian Molloy
Ben Edwards
AAML
VLM
91
463
0
03 Jul 2018
How To Backdoor Federated Learning
Eugene Bagdasaryan
Andreas Veit
Yiqing Hua
D. Estrin
Vitaly Shmatikov
SILM
FedML
158
1,943
0
02 Jul 2018
Adversarial Perturbations Against Real-Time Video Classification Systems
Shasha Li
Ajaya Neupane
S. Paul
Chengyu Song
S. Krishnamurthy
Amit K. Roy-Chowdhury
A. Swami
AAML
93
121
0
02 Jul 2018
Stochastic model-based minimization under high-order growth
Damek Davis
Dmitriy Drusvyatskiy
Kellie J. MacPhee
151
31
0
01 Jul 2018
Adversarial Examples in Deep Learning: Characterization and Divergence
Wenqi Wei
Ling Liu
Margaret Loper
Stacey Truex
Lei Yu
Mehmet Emre Gursoy
Yanzhao Wu
AAML
SILM
119
18
0
29 Jun 2018
A New Angle on L2 Regularization
T. Tanay
Lewis D. Griffin
LLMSV
50
5
0
28 Jun 2018
Adversarial Reprogramming of Neural Networks
Gamaleldin F. Elsayed
Ian Goodfellow
Jascha Narain Sohl-Dickstein
OOD
AAML
55
184
0
28 Jun 2018
Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning
J. Dhaliwal
S. Shintre
AAML
49
15
0
27 Jun 2018
On Adversarial Examples for Character-Level Neural Machine Translation
J. Ebrahimi
Daniel Lowd
Dejing Dou
AAML
94
223
0
23 Jun 2018
On the Spectral Bias of Neural Networks
Nasim Rahaman
A. Baratin
Devansh Arpit
Felix Dräxler
Min Lin
Fred Hamprecht
Yoshua Bengio
Aaron Courville
172
1,463
0
22 Jun 2018
Detection based Defense against Adversarial Examples from the Steganalysis Point of View
Jiayang Liu
Weiming Zhang
Yiwei Zhang
Dongdong Hou
Yujia Liu
Hongyue Zha
Nenghai Yu
AAML
101
100
0
21 Jun 2018
Gradient Adversarial Training of Neural Networks
Ayan Sinha
Zhao Chen
Vijay Badrinarayanan
Andrew Rabinovich
AAML
70
33
0
21 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks
David Alvarez-Melis
Tommi Jaakkola
MILM
XAI
140
948
0
20 Jun 2018
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations
T. Tanay
Jerone T. A. Andrews
Lewis D. Griffin
73
7
0
19 Jun 2018
Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning
Zecheng He
Aswin Raghavan
Guangyuan Hu
S. Chai
Ruby B. Lee
45
4
0
18 Jun 2018
Non-Negative Networks Against Adversarial Attacks
William Fleshman
Edward Raff
Jared Sylvester
Steven Forsyth
Mark McLean
AAML
66
41
0
15 Jun 2018
DeepLaser: Practical Fault Attack on Deep Neural Networks
J. Breier
Xiaolu Hou
Dirmanto Jap
Lei Ma
S. Bhasin
Yang Liu
AAML
AI4CE
80
19
0
15 Jun 2018
Hardware Trojan Attacks on Neural Networks
Joseph Clements
Yingjie Lao
AAML
78
89
0
14 Jun 2018
Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data
Jacson Rodrigues Correia-Silva
Rodrigo Berriel
C. Badue
Alberto F. de Souza
Thiago Oliveira-Santos
MLAU
86
175
0
14 Jun 2018
Hierarchical interpretations for neural network predictions
Chandan Singh
W. James Murdoch
Bin Yu
84
146
0
14 Jun 2018
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma
Alex Lamb
Christopher Beckham
Amir Najafi
Ioannis Mitliagkas
Aaron Courville
David Lopez-Paz
Yoshua Bengio
AAML
DRL
111
35
0
13 Jun 2018
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus
William Fleshman
Edward Raff
Richard Zak
Mark McLean
Charles K. Nicholas
AAML
49
34
0
12 Jun 2018
Adversarial Attacks on Variational Autoencoders
George Gondim-Ribeiro
Pedro Tabacof
Eduardo Valle
AAML
DRL
78
44
0
12 Jun 2018
Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks
Clemens Seibold
Wojciech Samek
Anna Hilsmann
Peter Eisert
AAML
CVBM
83
30
0
11 Jun 2018
Adversarial Meta-Learning
Chengxiang Yin
Jian Tang
Zhiyuan Xu
Yanzhi Wang
95
42
0
08 Jun 2018
Training Augmentation with Adversarial Examples for Robust Speech Recognition
Sining Sun
Ching-Feng Yeh
Mari Ostendorf
M. Hwang
Lei Xie
AAML
82
63
0
07 Jun 2018
Adversarial Attack on Graph Structured Data
H. Dai
Hui Li
Tian Tian
Xin Huang
L. Wang
Jun Zhu
Le Song
GNN
AAML
OOD
118
780
0
06 Jun 2018
Towards Dependability Metrics for Neural Networks
Chih-Hong Cheng
Georg Nührenberg
Chung-Hao Huang
Harald Ruess
Hirotoshi Yasuoka
85
44
0
06 Jun 2018
DPatch: An Adversarial Patch Attack on Object Detectors
Xin Liu
Huanrui Yang
Ziwei Liu
Linghao Song
Hai Helen Li
Yiran Chen
AAML
ObjD
72
293
0
05 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy
Lance M. Kaplan
M. Kandemir
OOD
UQCV
EDL
BDL
201
1,008
0
05 Jun 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
A. Salem
Yang Zhang
Mathias Humbert
Pascal Berrang
Mario Fritz
Michael Backes
MIACV
MIALM
171
955
0
04 Jun 2018
Neural Adversarial Training for Semi-supervised Japanese Predicate-argument Structure Analysis
Shuhei Kurita
Daisuke Kawahara
Sadao Kurohashi
37
12
0
04 Jun 2018
Detecting Adversarial Examples via Key-based Network
Pinlong Zhao
Zhouyu Fu
Ou Wu
Q. Hu
Jun Wang
AAML
GAN
59
8
0
02 Jun 2018
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Jan Svoboda
Jonathan Masci
Federico Monti
M. Bronstein
Leonidas Guibas
AAML
GNN
88
41
0
31 May 2018
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