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SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing

SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing

18 March 2020
Chawin Sitawarin
S. Chakraborty
David A. Wagner
    AAML
ArXivPDFHTML

Papers citing "SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing"

12 / 12 papers shown
Title
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing
  Adversarial Robustness
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness
Kejia Zhang
Juanjuan Weng
Junwei Wu
Guoqing Yang
Shaozi Li
Zhiming Luo
AAML
40
1
0
17 Jun 2024
Catastrophic Overfitting: A Potential Blessing in Disguise
Catastrophic Overfitting: A Potential Blessing in Disguise
Mengnan Zhao
Lihe Zhang
Yuqiu Kong
Baocai Yin
AAML
41
1
0
28 Feb 2024
Navigating Complexity: Toward Lossless Graph Condensation via Expanding
  Window Matching
Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching
Yuchen Zhang
Tianle Zhang
Kai Wang
Ziyao Guo
Yuxuan Liang
Xavier Bresson
Wei Jin
Yang You
32
23
0
07 Feb 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off
  in Adversarial Training
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda
Bahram Zonooz
Elahe Arani
AAML
31
2
0
26 Jan 2024
How Deep Learning Sees the World: A Survey on Adversarial Attacks &
  Defenses
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses
Joana Cabral Costa
Tiago Roxo
Hugo Manuel Proença
Pedro R. M. Inácio
AAML
37
49
0
18 May 2023
Robust Models are less Over-Confident
Robust Models are less Over-Confident
Julia Grabinski
Paul Gavrikov
J. Keuper
M. Keuper
AAML
28
24
0
12 Oct 2022
Adversarial Robustness through the Lens of Convolutional Filters
Adversarial Robustness through the Lens of Convolutional Filters
Paul Gavrikov
J. Keuper
30
15
0
05 Apr 2022
LAS-AT: Adversarial Training with Learnable Attack Strategy
LAS-AT: Adversarial Training with Learnable Attack Strategy
Xiaojun Jia
Yong Zhang
Baoyuan Wu
Ke Ma
Jue Wang
Xiaochun Cao
AAML
47
131
0
13 Mar 2022
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
194
345
0
15 Dec 2021
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial
  Robustness of Neural Networks
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks
Linhai Ma
Liang Liang
AAML
18
18
0
19 May 2020
Instance adaptive adversarial training: Improved accuracy tradeoffs in
  neural nets
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
Yogesh Balaji
Tom Goldstein
Judy Hoffman
AAML
131
103
0
17 Oct 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,888
0
15 Sep 2016
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