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Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset
  Selection

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection

8 February 2023
Xilie Xu
Jingfeng Zhang
Feng Liu
Masashi Sugiyama
Mohan S. Kankanhalli
    AAML
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Papers citing "Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection"

50 / 50 papers shown
Title
Enhancing Adversarial Contrastive Learning via Adversarial Invariant
  Regularization
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
Xilie Xu
Jingfeng Zhang
Feng Liu
Masashi Sugiyama
Mohan S. Kankanhalli
AAML
63
10
0
30 Apr 2023
Rethinking the Effect of Data Augmentation in Adversarial Contrastive
  Learning
Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning
Rundong Luo
Yifei Wang
Yisen Wang
41
26
0
02 Mar 2023
Efficient and Effective Augmentation Strategy for Adversarial Training
Efficient and Effective Augmentation Strategy for Adversarial Training
Sravanti Addepalli
Samyak Jain
R. Venkatesh Babu
AAML
87
60
0
27 Oct 2022
Adversarial Coreset Selection for Efficient Robust Training
Adversarial Coreset Selection for Efficient Robust Training
H. M. Dolatabadi
S. Erfani
C. Leckie
AAML
27
7
0
13 Sep 2022
Decoupled Adversarial Contrastive Learning for Self-supervised
  Adversarial Robustness
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Chaoning Zhang
Kang Zhang
Chenshuang Zhang
Axi Niu
Jiu Feng
Chang D. Yoo
In So Kweon
SSL
50
25
0
22 Jul 2022
Adversarial Contrastive Learning via Asymmetric InfoNCE
Adversarial Contrastive Learning via Asymmetric InfoNCE
Qiying Yu
Jieming Lou
Xianyuan Zhan
Qizhang Li
W. Zuo
Yang Liu
Jingjing Liu
AAML
46
23
0
18 Jul 2022
Adversarially Robust Models may not Transfer Better: Sufficient
  Conditions for Domain Transferability from the View of Regularization
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization
Xiaojun Xu
Jacky Y. Zhang
Evelyn Ma
Danny Son
Oluwasanmi Koyejo
Yue Liu
36
12
0
03 Feb 2022
Revisiting and Advancing Fast Adversarial Training Through The Lens of
  Bi-Level Optimization
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization
Yihua Zhang
Guanhua Zhang
Prashant Khanduri
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
57
87
0
23 Dec 2021
When Does Contrastive Learning Preserve Adversarial Robustness from
  Pretraining to Finetuning?
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Lijie Fan
Sijia Liu
Pin-Yu Chen
Gaoyuan Zhang
Chuang Gan
AAML
VLM
37
121
0
01 Nov 2021
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised
  Learning
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
Krishnateja Killamsetty
Xujiang Zhao
F. Chen
Rishabh K. Iyer
52
81
0
14 Jun 2021
ImageNet-21K Pretraining for the Masses
ImageNet-21K Pretraining for the Masses
T. Ridnik
Emanuel Ben-Baruch
Asaf Noy
Lihi Zelnik-Manor
SSeg
VLM
CLIP
265
692
0
22 Apr 2021
An Empirical Study of Training Self-Supervised Vision Transformers
An Empirical Study of Training Self-Supervised Vision Transformers
Xinlei Chen
Saining Xie
Kaiming He
ViT
98
1,837
0
05 Apr 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient
  Deep Model Training
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty
D. Sivasubramanian
Ganesh Ramakrishnan
A. De
Rishabh K. Iyer
OOD
108
197
0
27 Feb 2021
GLISTER: Generalization based Data Subset Selection for Efficient and
  Robust Learning
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning
Krishnateja Killamsetty
D. Sivasubramanian
Ganesh Ramakrishnan
Rishabh Iyer University of Texas at Dallas
39
205
0
19 Dec 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
151
3,992
0
20 Nov 2020
Robust Pre-Training by Adversarial Contrastive Learning
Robust Pre-Training by Adversarial Contrastive Learning
Ziyu Jiang
Tianlong Chen
Ting-Li Chen
Zhangyang Wang
62
230
0
26 Oct 2020
Contrastive Learning with Adversarial Examples
Contrastive Learning with Adversarial Examples
Chih-Hui Ho
Nuno Vasconcelos
SSL
29
142
0
22 Oct 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
159
40,217
0
22 Oct 2020
Representation Learning via Invariant Causal Mechanisms
Representation Learning via Invariant Causal Mechanisms
Jovana Mitrović
Brian McWilliams
Jacob Walker
Lars Buesing
Charles Blundell
CML
OOD
SSL
48
248
0
15 Oct 2020
Contrastive Representation Learning: A Framework and Review
Contrastive Representation Learning: A Framework and Review
Phúc H. Lê Khắc
Graham Healy
Alan F. Smeaton
SSL
AI4TS
218
697
0
10 Oct 2020
Do Adversarially Robust ImageNet Models Transfer Better?
Do Adversarially Robust ImageNet Models Transfer Better?
Hadi Salman
Andrew Ilyas
Logan Engstrom
Ashish Kapoor
Aleksander Madry
51
423
0
16 Jul 2020
Understanding and Improving Fast Adversarial Training
Understanding and Improving Fast Adversarial Training
Maksym Andriushchenko
Nicolas Flammarion
AAML
48
286
0
06 Jul 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
233
6,718
0
13 Jun 2020
Adversarial Self-Supervised Contrastive Learning
Adversarial Self-Supervised Contrastive Learning
Minseon Kim
Jihoon Tack
Sung Ju Hwang
SSL
47
249
0
13 Jun 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
364
41,106
0
28 May 2020
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic
  Lesions Segmentation
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation
Jiahua Dong
Yang Cong
Gan Sun
Bineng Zhong
Xiaowei Xu
28
138
0
24 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of
  diverse parameter-free attacks
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
177
1,821
0
03 Mar 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang
Xilie Xu
Bo Han
Gang Niu
Li-zhen Cui
Masashi Sugiyama
Mohan S. Kankanhalli
AAML
39
400
0
26 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
144
18,523
0
13 Feb 2020
Fast is better than free: Revisiting adversarial training
Fast is better than free: Revisiting adversarial training
Eric Wong
Leslie Rice
J. Zico Kolter
AAML
OOD
118
1,167
0
12 Jan 2020
Square Attack: a query-efficient black-box adversarial attack via random
  search
Square Attack: a query-efficient black-box adversarial attack via random search
Maksym Andriushchenko
Francesco Croce
Nicolas Flammarion
Matthias Hein
AAML
49
977
0
29 Nov 2019
Adversarial Examples Improve Image Recognition
Adversarial Examples Improve Image Recognition
Cihang Xie
Mingxing Tan
Boqing Gong
Jiang Wang
Alan Yuille
Quoc V. Le
AAML
58
564
0
21 Nov 2019
A Large-scale Study of Representation Learning with the Visual Task
  Adaptation Benchmark
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
Xiaohua Zhai
J. Puigcerver
Alexander Kolesnikov
P. Ruyssen
C. Riquelme
...
Michael Tschannen
Marcin Michalski
Olivier Bousquet
Sylvain Gelly
N. Houlsby
SSL
49
432
0
01 Oct 2019
Defense Against Adversarial Attacks Using Feature Scattering-based
  Adversarial Training
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang
Jianyu Wang
AAML
50
230
0
24 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary
  Attack
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce
Matthias Hein
AAML
70
482
0
03 Jul 2019
Are Labels Required for Improving Adversarial Robustness?
Are Labels Required for Improving Adversarial Robustness?
J. Uesato
Jean-Baptiste Alayrac
Po-Sen Huang
Robert Stanforth
Alhussein Fawzi
Pushmeet Kohli
AAML
43
333
0
31 May 2019
Adversarial Training for Free!
Adversarial Training for Free!
Ali Shafahi
Mahyar Najibi
Amin Ghiasi
Zheng Xu
John P. Dickerson
Christoph Studer
L. Davis
Gavin Taylor
Tom Goldstein
AAML
97
1,238
0
29 Apr 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
49
726
0
28 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
92
2,525
0
24 Jan 2019
Non-submodular Function Maximization subject to a Matroid Constraint,
  with Applications
Non-submodular Function Maximization subject to a Matroid Constraint, with Applications
Khashayar Gatmiry
Manuel Gomez Rodriguez
41
7
0
19 Nov 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
145
3,171
0
01 Feb 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
182
11,962
0
19 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and
  Semi-Supervised Learning
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato
S. Maeda
Masanori Koyama
S. Ishii
GAN
102
2,724
0
13 Apr 2017
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
194
8,030
0
13 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
480
5,868
0
08 Jul 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
215
7,951
0
23 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.0K
192,638
0
10 Dec 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
124
18,922
0
20 Dec 2014
Submodular meets Spectral: Greedy Algorithms for Subset Selection,
  Sparse Approximation and Dictionary Selection
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Abhimanyu Das
David Kempe
97
485
0
19 Feb 2011
Adaptive Submodularity: Theory and Applications in Active Learning and
  Stochastic Optimization
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization
Daniel Golovin
Andreas Krause
125
600
0
21 Mar 2010
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