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2111.13244
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Going Grayscale: The Road to Understanding and Improving Unlearnable Examples
25 November 2021
Zhuoran Liu
Zhengyu Zhao
A. Kolmus
Tijn Berns
Twan van Laarhoven
Tom Heskes
Martha Larson
AAML
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Papers citing
"Going Grayscale: The Road to Understanding and Improving Unlearnable Examples"
20 / 20 papers shown
Title
Adversarial Examples Make Strong Poisons
Liam H. Fowl
Micah Goldblum
Ping Yeh-Chiang
Jonas Geiping
Wojtek Czaja
Tom Goldstein
SILM
62
134
0
21 Jun 2021
Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang
Xingjun Ma
S. Erfani
James Bailey
Yisen Wang
MIACV
195
192
0
13 Jan 2021
Large image datasets: A pyrrhic win for computer vision?
Vinay Uday Prabhu
Abeba Birhane
41
362
0
24 Jun 2020
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
153
2,023
0
16 Apr 2020
MetaPoison: Practical General-purpose Clean-label Data Poisoning
Wenjie Huang
Jonas Geiping
Liam H. Fowl
Gavin Taylor
Tom Goldstein
91
188
0
01 Apr 2020
Functional Adversarial Attacks
Cassidy Laidlaw
Soheil Feizi
AAML
46
184
0
29 May 2019
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban
Ching-An Cheng
Nathan Hatch
Byron Boots
74
265
0
25 Oct 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi
P. Frasconi
Saverio Salzo
Riccardo Grazzi
Massimiliano Pontil
168
722
0
13 Jun 2018
Is feature selection secure against training data poisoning?
Huang Xiao
Battista Biggio
Gavin Brown
Giorgio Fumera
Claudia Eckert
Fabio Roli
AAML
SILM
33
423
0
21 Apr 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Xinyun Chen
Chang-rui Liu
Yue Liu
Kimberly Lu
D. Song
AAML
SILM
78
1,822
0
15 Dec 2017
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
221
9,687
0
25 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
203
11,962
0
19 Jun 2017
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images
Rakshith Shetty
Bernt Schiele
Mario Fritz
75
226
0
30 Mar 2017
Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective
Seong Joon Oh
Mario Fritz
Bernt Schiele
CVBM
AAML
377
160
0
28 Mar 2017
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
132
2,854
0
14 Mar 2017
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
151
8,497
0
16 Aug 2016
Faceless Person Recognition; Privacy Implications in Social Media
Seong Joon Oh
Rodrigo Benenson
Mario Fritz
Bernt Schiele
CVBM
351
154
0
28 Jul 2016
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
148
18,922
0
20 Dec 2014
Deep Learning in Neural Networks: An Overview
Jürgen Schmidhuber
HAI
153
16,311
0
30 Apr 2014
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
150
14,831
1
21 Dec 2013
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