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Certifying Joint Adversarial Robustness for Model Ensembles

Certifying Joint Adversarial Robustness for Model Ensembles

21 April 2020
M. Jonas
David Evans
    AAML
ArXivPDFHTML

Papers citing "Certifying Joint Adversarial Robustness for Model Ensembles"

27 / 27 papers shown
Title
Denoised Smoothing: A Provable Defense for Pretrained Classifiers
Denoised Smoothing: A Provable Defense for Pretrained Classifiers
Hadi Salman
Mingjie Sun
Greg Yang
Ashish Kapoor
J. Zico Kolter
48
23
0
04 Mar 2020
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
179
827
0
19 Feb 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building
  Adversarial Defense
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense
Meng
Jianhai Su
Jason M. O'Kane
Pooyan Jamshidi
AAML
21
7
0
02 Jan 2020
$n$-ML: Mitigating Adversarial Examples via Ensembles of Topologically
  Manipulated Classifiers
nnn-ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers
Mahmood Sharif
Lujo Bauer
Michael K. Reiter
AAML
28
6
0
19 Dec 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
94
2,018
0
08 Feb 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang
Kun Xu
Chao Du
Ning Chen
Jun Zhu
AAML
57
435
0
25 Jan 2019
Cost-Sensitive Robustness against Adversarial Examples
Cost-Sensitive Robustness against Adversarial Examples
Xiao Zhang
David Evans
AAML
38
25
0
22 Oct 2018
The Curse of Concentration in Robust Learning: Evasion and Poisoning
  Attacks from Concentration of Measure
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
Saeed Mahloujifar
Dimitrios I. Diochnos
Mohammad Mahmoody
43
150
0
09 Sep 2018
Are adversarial examples inevitable?
Are adversarial examples inevitable?
Ali Shafahi
Wenjie Huang
Christoph Studer
Soheil Feizi
Tom Goldstein
SILM
46
282
0
06 Sep 2018
Adversarially Robust Generalization Requires More Data
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt
Shibani Santurkar
Dimitris Tsipras
Kunal Talwar
Aleksander Madry
OOD
AAML
114
786
0
30 Apr 2018
Adversarial vulnerability for any classifier
Adversarial vulnerability for any classifier
Alhussein Fawzi
Hamza Fawzi
Omar Fawzi
AAML
65
248
0
23 Feb 2018
Certified Defenses against Adversarial Examples
Certified Defenses against Adversarial Examples
Aditi Raghunathan
Jacob Steinhardt
Percy Liang
AAML
83
967
0
29 Jan 2018
Mitigating Adversarial Effects Through Randomization
Mitigating Adversarial Effects Through Randomization
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Zhou Ren
Alan Yuille
AAML
80
1,050
0
06 Nov 2017
Provable defenses against adversarial examples via the convex outer
  adversarial polytope
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong
J. Zico Kolter
AAML
78
1,495
0
02 Nov 2017
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
93
2,140
0
21 Aug 2017
Robust Physical-World Attacks on Deep Learning Models
Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Chaowei Xiao
Atul Prakash
Tadayoshi Kohno
D. Song
AAML
37
594
0
27 Jul 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
211
11,962
0
19 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples
MagNet: a Two-Pronged Defense against Adversarial Examples
Dongyu Meng
Hao Chen
AAML
28
1,205
0
25 May 2017
Ensemble Adversarial Training: Attacks and Defenses
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr
Alexey Kurakin
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
165
2,712
0
19 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural
  Networks
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu
David Evans
Yanjun Qi
AAML
48
1,248
0
04 Apr 2017
Detecting Adversarial Samples from Artifacts
Detecting Adversarial Samples from Artifacts
Reuben Feinman
Ryan R. Curtin
S. Shintre
Andrew B. Gardner
AAML
71
892
0
01 Mar 2017
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
157
8,497
0
16 Aug 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.3K
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
60
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
90
4,878
0
14 Nov 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
158
18,922
0
20 Dec 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
159
14,831
1
21 Dec 2013
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