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Improving Ensemble Robustness by Collaboratively Promoting and Demoting
  Adversarial Robustness

Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness

21 September 2020
Tuan-Anh Bui
Trung Le
He Zhao
Paul Montague
O. deVel
Tamas Abraham
Dinh Q. Phung
    AAML
    FedML
ArXivPDFHTML

Papers citing "Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness"

4 / 4 papers shown
Title
Bayesian posterior approximation with stochastic ensembles
Bayesian posterior approximation with stochastic ensembles
Oleksandr Balabanov
Bernhard Mehlig
H. Linander
BDL
UQCV
27
5
0
15 Dec 2022
A Unified Wasserstein Distributional Robustness Framework for
  Adversarial Training
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Tu Bui
Trung Le
Quan Hung Tran
He Zhao
Dinh Q. Phung
AAML
OOD
36
42
0
27 Feb 2022
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial
  Robustness of Neural Networks
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks
Linhai Ma
Liang Liang
AAML
26
18
0
19 May 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,842
0
08 Jul 2016
1