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Simulating Unknown Target Models for Query-Efficient Black-box Attacks

Simulating Unknown Target Models for Query-Efficient Black-box Attacks

2 September 2020
Chen Ma
L. Chen
Junhai Yong
    MLAU
    OOD
ArXivPDFHTML

Papers citing "Simulating Unknown Target Models for Query-Efficient Black-box Attacks"

5 / 5 papers shown
Title
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Saeed Mian
Navid Kardan
M. Shah
AAML
22
235
0
01 Aug 2021
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Minhao Cheng
Simranjit Singh
Patrick H. Chen
Pin-Yu Chen
Sijia Liu
Cho-Jui Hsieh
AAML
122
219
0
24 Sep 2019
ComDefend: An Efficient Image Compression Model to Defend Adversarial
  Examples
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples
Xiaojun Jia
Xingxing Wei
Xiaochun Cao
H. Foroosh
AAML
50
264
0
30 Nov 2018
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
252
11,677
0
09 Mar 2017
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
270
10,214
0
16 Nov 2016
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