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Art-Attack: Black-Box Adversarial Attack via Evolutionary Art

Art-Attack: Black-Box Adversarial Attack via Evolutionary Art

7 March 2022
P. Williams
Ke Li
    AAML
ArXiv (abs)PDFHTML

Papers citing "Art-Attack: Black-Box Adversarial Attack via Evolutionary Art"

42 / 42 papers shown
Title
Interpretability in deep learning for finance: a case study for the
  Heston model
Interpretability in deep learning for finance: a case study for the Heston model
D. Brigo
Xiaoshan Huang
A. Pallavicini
Haitz Sáez de Ocáriz Borde
FAtt
32
9
0
19 Apr 2021
An Improved Two-Archive Evolutionary Algorithm for Constrained
  Multi-Objective Optimization
An Improved Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization
X. Shan
Ke Li
44
20
0
10 Mar 2021
Recent Advances in Adversarial Training for Adversarial Robustness
Recent Advances in Adversarial Training for Adversarial Robustness
Tao Bai
Jinqi Luo
Jun Zhao
Bihan Wen
Qian Wang
AAML
129
493
0
02 Feb 2021
Sparse-RS: a versatile framework for query-efficient sparse black-box
  adversarial attacks
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce
Maksym Andriushchenko
Naman D. Singh
Nicolas Flammarion
Matthias Hein
83
101
0
23 Jun 2020
On the Combined Impact of Population Size and Sub-problem Selection in
  MOEA/D
On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D
Geoffrey Pruvost
B. Derbel
A. Liefooghe
Ke Li
Qingfu Zhang
26
13
0
15 Apr 2020
Adversarial Examples for Models of Code
Adversarial Examples for Models of Code
Noam Yefet
Uri Alon
Eran Yahav
SILMAAMLMLAU
78
166
0
15 Oct 2019
Yet another but more efficient black-box adversarial attack: tiling and
  evolution strategies
Yet another but more efficient black-box adversarial attack: tiling and evolution strategies
Laurent Meunier
Cen Chen
Li Wang
MLAUAAML
118
40
0
05 Oct 2019
Black-box Adversarial Attacks with Bayesian Optimization
Black-box Adversarial Attacks with Bayesian Optimization
Satya Narayan Shukla
Anit Kumar Sahu
Devin Willmott
J. Zico Kolter
AAMLMLAU
49
31
0
30 Sep 2019
Does Preference Always Help? A Holistic Study on Preference-Based
  Evolutionary Multi-Objective Optimisation Using Reference Points
Does Preference Always Help? A Holistic Study on Preference-Based Evolutionary Multi-Objective Optimisation Using Reference Points
Ke Li
Minhui Liao
Kalyanmoy Deb
Geyong Min
Xin Yao
57
58
0
30 Sep 2019
Bayesian Network Based Label Correlation Analysis For Multi-label
  Classifier Chain
Bayesian Network Based Label Correlation Analysis For Multi-label Classifier Chain
Ran Wang
Suhe Ye
Ke Li
Sam Kwong
49
50
0
06 Aug 2019
Improving Black-box Adversarial Attacks with a Transfer-based Prior
Improving Black-box Adversarial Attacks with a Transfer-based Prior
Shuyu Cheng
Yinpeng Dong
Tianyu Pang
Hang Su
Jun Zhu
AAML
78
274
0
17 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient
  Black-box Attacks
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
Ziang Yan
Yiwen Guo
Changshui Zhang
AAML
62
111
0
11 Jun 2019
Simple Black-box Adversarial Attacks
Simple Black-box Adversarial Attacks
Chuan Guo
Jacob R. Gardner
Yurong You
A. Wilson
Kilian Q. Weinberger
AAML
62
579
0
17 May 2019
Visualisation of Pareto Front Approximation: A Short Survey and
  Empirical Comparisons
Visualisation of Pareto Front Approximation: A Short Survey and Empirical Comparisons
Huiru Gao
Haifeng Nie
Ke Li
45
37
0
05 Mar 2019
Which Surrogate Works for Empirical Performance Modelling? A Case Study
  with Differential Evolution
Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution
Ke Li
Zilin Xiang
Kay Chen Tan
44
28
0
30 Jan 2019
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial
  Attacks
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks
T. Brunner
Frederik Diehl
Michael Truong-Le
Alois Knoll
MLAUAAML
75
117
0
24 Dec 2018
Low Frequency Adversarial Perturbation
Low Frequency Adversarial Perturbation
Chuan Guo
Jared S. Frank
Kilian Q. Weinberger
AAML
63
166
0
24 Sep 2018
Query-Efficient Hard-label Black-box Attack:An Optimization-based
  Approach
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
103
348
0
12 Jul 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for
  Attacking Black-box Neural Networks
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
Chun-Chen Tu
Pai-Shun Ting
Pin-Yu Chen
Sijia Liu
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
Shin-Ming Cheng
MLAUAAML
84
398
0
30 May 2018
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization
M. Alzantot
Yash Sharma
Supriyo Chakraborty
Huan Zhang
Cho-Jui Hsieh
Mani B. Srivastava
AAML
77
258
0
28 May 2018
Black-box Adversarial Attacks with Limited Queries and Information
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas
Logan Engstrom
Anish Athalye
Jessy Lin
MLAUAAML
163
1,204
0
23 Apr 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
J. Uesato
Brendan O'Donoghue
Aaron van den Oord
Pushmeet Kohli
AAML
160
606
0
15 Feb 2018
Interactive Decomposition Multi-Objective Optimization via Progressively
  Learned Value Functions
Interactive Decomposition Multi-Objective Optimization via Progressively Learned Value Functions
Ke Li
Renzhi Chen
D. Savić
Xin Yao
54
56
0
02 Jan 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box
  Machine Learning Models
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Wieland Brendel
Jonas Rauber
Matthias Bethge
AAML
67
1,350
0
12 Dec 2017
Attacking the Madry Defense Model with $L_1$-based Adversarial Examples
Attacking the Madry Defense Model with L1L_1L1​-based Adversarial Examples
Yash Sharma
Pin-Yu Chen
88
118
0
30 Oct 2017
One pixel attack for fooling deep neural networks
One pixel attack for fooling deep neural networks
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
127
2,327
0
24 Oct 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial
  Examples
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Pin-Yu Chen
Yash Sharma
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
AAML
66
641
0
13 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
83
1,882
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
SILMOOD
310
12,117
0
19 Jun 2017
Black-Box Attacks against RNN based Malware Detection Algorithms
Black-Box Attacks against RNN based Malware Detection Algorithms
Weiwei Hu
Ying Tan
44
150
0
23 May 2017
Evolutionary Many-Objective Optimization Based on Adversarial
  Decomposition
Evolutionary Many-Objective Optimization Based on Adversarial Decomposition
Mengyuan Wu
Ke Li
Sam Kwong
Qingfu Zhang
47
105
0
07 Apr 2017
Dynamic Multi-Objectives Optimization with a Changing Number of
  Objectives
Dynamic Multi-Objectives Optimization with a Changing Number of Objectives
Renzhi Chen
Ke Li
Xin Yao
53
172
0
23 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
266
8,579
0
16 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
545
5,909
0
08 Jul 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
114
1,742
0
24 May 2016
End to End Learning for Self-Driving Cars
End to End Learning for Self-Driving Cars
Mariusz Bojarski
D. Testa
Daniel Dworakowski
Bernhard Firner
B. Flepp
...
Urs Muller
Jiakai Zhang
Xin Zhang
Jake Zhao
Karol Zieba
SSL
100
4,175
0
25 Apr 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,260
0
22 Dec 2014
Striving for Simplicity: The All Convolutional Net
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
248
4,681
0
21 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
280
19,107
0
20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,479
0
04 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
277
14,961
1
21 Dec 2013
Network In Network
Network In Network
Min Lin
Qiang Chen
Shuicheng Yan
294
6,283
0
16 Dec 2013
1