ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2206.03353
  4. Cited By
Improving Adversarial Robustness by Putting More Regularizations on Less
  Robust Samples
v1v2v3v4 (latest)

Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples

International Conference on Machine Learning (ICML), 2022
7 June 2022
Dongyoon Yang
Insung Kong
Yongdai Kim
    OODAAML
ArXiv (abs)PDFHTMLGithub (3★)

Papers citing "Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples"

11 / 11 papers shown
Zero-Shot Robustness of Vision Language Models Via Confidence-Aware Weighting
Zero-Shot Robustness of Vision Language Models Via Confidence-Aware Weighting
Nikoo Naghavian
Mostafa Tavassolipour
AAMLVLM
187
0
0
03 Oct 2025
Robustness Feature Adapter for Efficient Adversarial Training
Robustness Feature Adapter for Efficient Adversarial Training
Quanwei Wu
Jun Guo
Wei Wang
Yi Alice Wang
AAML
176
1
0
25 Aug 2025
Sharpness-Aware Geometric Defense for Robust Out-Of-Distribution Detection
Sharpness-Aware Geometric Defense for Robust Out-Of-Distribution Detection
Jeng-Lin Li
Ming-Ching Chang
Wei-Chao Chen
181
0
0
24 Aug 2025
TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification
TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical JustificationComputer Vision and Pattern Recognition (CVPR), 2025
Dongyoon Yang
Jihu Lee
Yongdai Kim
350
1
0
10 May 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-OffsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Kasimir Tanner
Matteo Vilucchio
Bruno Loureiro
Florent Krzakala
AAML
483
4
0
31 Dec 2024
Adversarial Training in Low-Label Regimes with Margin-Based
  Interpolation
Adversarial Training in Low-Label Regimes with Margin-Based Interpolation
Tian Ye
Rajgopal Kannan
Viktor Prasanna
AAML
347
0
0
27 Nov 2024
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional
  Adversarial Training
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training
Junhao Dong
Xinghua Qu
Zhiyuan Wang
Yew-Soon Ong
AAML
287
4
0
05 Nov 2024
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial TrainingIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2024
Tejaswini Medi
Steffen Jung
Margret Keuper
AAML
521
5
0
30 Oct 2024
ADBM: Adversarial diffusion bridge model for reliable adversarial purification
ADBM: Adversarial diffusion bridge model for reliable adversarial purificationInternational Conference on Learning Representations (ICLR), 2024
Xiao-Li Li
Wenxuan Sun
Huanran Chen
Qiongxiu Li
Yining Liu
Yingzhe He
Jie Shi
Xiaolin Hu
AAML
765
28
0
01 Aug 2024
Defenses in Adversarial Machine Learning: A Survey
Defenses in Adversarial Machine Learning: A Survey
Baoyuan Wu
Shaokui Wei
Mingli Zhu
Meixi Zheng
Zihao Zhu
Ruotong Wang
Hongrui Chen
Danni Yuan
Li Liu
Qingshan Liu
AAML
367
31
0
13 Dec 2023
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively
  Weighted Regularization and Knowledge Distillation
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge DistillationIEEE International Conference on Computer Vision (ICCV), 2023
Dongyoon Yang
Insung Kong
Yongdai Kim
267
6
0
08 Aug 2023
1
Page 1 of 1