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A Minimax Approach Against Multi-Armed Adversarial Attacks Detection

A Minimax Approach Against Multi-Armed Adversarial Attacks Detection

4 February 2023
Federica Granese
Marco Romanelli
S. Garg
Pablo Piantanida
    AAML
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Papers citing "A Minimax Approach Against Multi-Armed Adversarial Attacks Detection"

5 / 5 papers shown
Title
MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples
  Detectors
MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors
Federica Granese
Marine Picot
Marco Romanelli
Francisco Messina
Pablo Piantanida
AAML
45
3
0
30 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
36
16
0
28 Jun 2022
Adversarial Robustness with Semi-Infinite Constrained Learning
Adversarial Robustness with Semi-Infinite Constrained Learning
Alexander Robey
Luiz F. O. Chamon
George J. Pappas
Hamed Hassani
Alejandro Ribeiro
AAML
OOD
118
42
0
29 Oct 2021
Understanding Failures in Out-of-Distribution Detection with Deep
  Generative Models
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily H. Zhang
Mark Goldstein
Rajesh Ranganath
OODD
143
103
0
14 Jul 2021
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
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