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Understanding and Combating Robust Overfitting via Input Loss Landscape
  Analysis and Regularization

Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization

9 December 2022
Lin Li
Michael W. Spratling
    AAML
ArXivPDFHTML

Papers citing "Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization"

5 / 5 papers shown
Title
Certified Robust Neural Networks: Generalization and Corruption
  Resistance
Certified Robust Neural Networks: Generalization and Corruption Resistance
Amine Bennouna
Ryan Lucas
Bart P. G. Van Parys
22
10
0
03 Mar 2023
Data Augmentation Alone Can Improve Adversarial Training
Data Augmentation Alone Can Improve Adversarial Training
Lin Li
Michael W. Spratling
16
49
0
24 Jan 2023
A Survey of Robust Adversarial Training in Pattern Recognition:
  Fundamental, Theory, and Methodologies
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OOD
AAML
ObjD
44
71
0
26 Mar 2022
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
256
3,102
0
04 Nov 2016
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
279
39,083
0
01 Sep 2014
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