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MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

6 August 2019
Chen Ma
Chenxu Zhao
Hailin Shi
Li Chen
Junhai Yong
Dan Zeng
    AAML
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Papers citing "MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks"

4 / 4 papers shown
Title
Simulating Unknown Target Models for Query-Efficient Black-box Attacks
Simulating Unknown Target Models for Query-Efficient Black-box Attacks
Chen Ma
L. Chen
Junhai Yong
MLAU
OOD
41
17
0
02 Sep 2020
Defending Adversarial Examples via DNN Bottleneck Reinforcement
Defending Adversarial Examples via DNN Bottleneck Reinforcement
Wenqing Liu
Miaojing Shi
Teddy Furon
Li Li
AAML
15
8
0
12 Aug 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
338
11,684
0
09 Mar 2017
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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