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1712.04006
Cited By
Training Ensembles to Detect Adversarial Examples
11 December 2017
Alexander Bagnall
Razvan Bunescu
Gordon Stewart
AAML
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Papers citing
"Training Ensembles to Detect Adversarial Examples"
22 / 22 papers shown
Title
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
Lei Zhang
Yuhang Zhou
Yi Yang
Xinbo Gao
AAML
OOD
46
7
0
04 Apr 2024
Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay
Yuhang Zhou
Zhongyun Hua
AAML
CLL
43
3
0
02 Apr 2024
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training
Saurabh Farkya
Aswin Raghavan
Avi Ziskind
14
0
0
30 Nov 2023
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
Zexu Sun
Bowei He
Ming Ma
Jiakai Tang
Yuchen Wang
Chen Ma
Dugang Liu
34
4
0
07 Oct 2023
Defending Adversarial Examples by Negative Correlation Ensemble
Wenjian Luo
Hongwei Zhang
Linghao Kong
Zhijian Chen
Jiaheng Zhang
AAML
20
1
0
11 Jun 2022
Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances
D. Steinberg
P. Munro
AAML
16
0
0
13 Nov 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney
Ehsan Abbasnejad
Simon Lucey
Anton Van Den Hengel
51
87
0
12 May 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
27
4
0
27 Mar 2021
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis
Nathan G. Drenkow
Neil Fendley
Philippe Burlina
AAML
27
2
0
11 Dec 2020
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
Huanrui Yang
Jingyang Zhang
Hongliang Dong
Nathan Inkawhich
Andrew B. Gardner
Andrew Touchet
Wesley Wilkes
Heath Berry
H. Li
AAML
23
107
0
30 Sep 2020
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness
Tuan-Anh Bui
Trung Le
He Zhao
Paul Montague
O. deVel
Tamas Abraham
Dinh Q. Phung
AAML
FedML
26
11
0
21 Sep 2020
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks
Kishor Datta Gupta
Zahid Akhtar
D. Dasgupta
AAML
27
9
0
01 Jul 2020
Evaluating Ensemble Robustness Against Adversarial Attacks
George Adam
Romain Speciel
AAML
SILM
14
4
0
12 May 2020
Playing to Learn Better: Repeated Games for Adversarial Learning with Multiple Classifiers
P. Dasgupta
J. B. Collins
Michael McCarrick
AAML
16
1
0
10 Feb 2020
Lower Bounds on Adversarial Robustness from Optimal Transport
A. Bhagoji
Daniel Cullina
Prateek Mittal
OOD
OT
AAML
29
92
0
26 Sep 2019
Defeating Misclassification Attacks Against Transfer Learning
Bang Wu
Shuo Wang
Xingliang Yuan
Cong Wang
Carsten Rudolph
Xiangwen Yang
AAML
16
6
0
29 Aug 2019
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness
Ling Liu
Wenqi Wei
Ka-Ho Chow
Margaret Loper
Emre Gursoy
Stacey Truex
Yanzhao Wu
UQCV
AAML
FedML
8
59
0
29 Aug 2019
Improving Adversarial Robustness of Ensembles with Diversity Training
Sanjay Kariyappa
Moinuddin K. Qureshi
AAML
FedML
17
133
0
28 Jan 2019
Exploiting the Inherent Limitation of L0 Adversarial Examples
F. Zuo
Bokai Yang
Xiaopeng Li
Lannan Luo
Qiang Zeng
AAML
21
1
0
23 Dec 2018
PAC-learning in the presence of evasion adversaries
Daniel Cullina
A. Bhagoji
Prateek Mittal
AAML
30
53
0
05 Jun 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch
João Monteiro
Isabela Albuquerque
Zahid Akhtar
T. Falk
AAML
38
29
0
21 Feb 2018
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
308
5,842
0
08 Jul 2016
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