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Randomized Adversarial Training via Taylor Expansion

Randomized Adversarial Training via Taylor Expansion

19 March 2023
Gao Jin
Xinping Yi
Dengyu Wu
Ronghui Mu
Xiaowei Huang
    AAML
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Papers citing "Randomized Adversarial Training via Taylor Expansion"

24 / 24 papers shown
Title
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Yi Yu
Song Xia
Xun Lin
Chenqi Kong
Wenhan Yang
Shijian Lu
Yap-Peng Tan
Alex C. Kot
AAML
SILM
145
0
0
20 Apr 2025
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho
Hongsin Lee
Changick Kim
AAML
TTA
176
0
0
09 Mar 2025
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Olukorede Fakorede
Modeste Atsague
Jin Tian
AAML
37
0
0
31 Dec 2024
Adversarial Training: A Survey
Adversarial Training: A Survey
Mengnan Zhao
Lihe Zhang
Jingwen Ye
Huchuan Lu
Baocai Yin
Xinchao Wang
AAML
28
0
0
19 Oct 2024
Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object
  Detectors
Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors
Tao Lin
Lijia Yu
Gaojie Jin
Renjue Li
Peng Wu
Lijun Zhang
AAML
30
1
0
14 Oct 2024
Adversarial Robustness Overestimation and Instability in TRADES
Adversarial Robustness Overestimation and Instability in TRADES
Jonathan Weiping Li
Ren-Wei Liang
Cheng-Han Yeh
Cheng-Chang Tsai
Kuanchun Yu
Chun-Shien Lu
Shang-Tse Chen
AAML
53
0
0
10 Oct 2024
Privacy-preserving Universal Adversarial Defense for Black-box Models
Privacy-preserving Universal Adversarial Defense for Black-box Models
Qiao Li
Cong Wu
Jing Chen
Zijun Zhang
Kun He
Ruiying Du
Xinxin Wang
Qingchuang Zhao
Yang Liu
AAML
63
6
0
20 Aug 2024
Resilience and Security of Deep Neural Networks Against Intentional and
  Unintentional Perturbations: Survey and Research Challenges
Resilience and Security of Deep Neural Networks Against Intentional and Unintentional Perturbations: Survey and Research Challenges
Sazzad Sayyed
Milin Zhang
Shahriar Rifat
A. Swami
Michael De Lucia
Francesco Restuccia
28
1
0
31 Jul 2024
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness
Kejia Zhang
Juanjuan Weng
Yuanzheng Cai
Zhiming Luo
Shaozi Li
AAML
59
0
0
04 Jul 2024
Artificial Immune System of Secure Face Recognition Against Adversarial
  Attacks
Artificial Immune System of Secure Face Recognition Against Adversarial Attacks
Min Ren
Yunlong Wang
Yuhao Zhu
Yongzhen Huang
Zhenan Sun
Qi Li
Tieniu Tan
43
2
0
26 Jun 2024
Revisiting the Adversarial Robustness of Vision Language Models: a
  Multimodal Perspective
Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective
Wanqi Zhou
Shuanghao Bai
Qibin Zhao
Badong Chen
VLM
AAML
44
5
0
30 Apr 2024
Are Classification Robustness and Explanation Robustness Really Strongly
  Correlated? An Analysis Through Input Loss Landscape
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
Tiejin Chen
Wenwang Huang
Linsey Pang
Dongsheng Luo
Hua Wei
OOD
43
0
0
09 Mar 2024
Towards Fairness-Aware Adversarial Learning
Towards Fairness-Aware Adversarial Learning
Yanghao Zhang
Tianle Zhang
Ronghui Mu
Xiaowei Huang
Wenjie Ruan
29
4
0
27 Feb 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
Mingda Zhang
Hongrui Chen
Danni Yuan
Li Liu
Qingshan Liu
AAML
30
14
0
13 Dec 2023
Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial
  Training
Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training
Qian Li
Yuxiao Hu
Yinpeng Dong
Dong-juan Zhang
Yuntian Chen
AAML
34
3
0
12 Dec 2023
Reward Certification for Policy Smoothed Reinforcement Learning
Reward Certification for Policy Smoothed Reinforcement Learning
Ronghui Mu
Leandro Soriano Marcolino
Tianle Zhang
Yanghao Zhang
Xiaowei Huang
Wenjie Ruan
28
4
0
11 Dec 2023
Indirect Gradient Matching for Adversarial Robust Distillation
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee
Seungju Cho
Changick Kim
AAML
FedML
53
2
0
06 Dec 2023
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory
  Prediction Models
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models
Liang Zhang
Nathaniel Xu
Pengfei Yang
Gao Jin
Cheng-Chao Huang
Lijun Zhang
28
8
0
11 Aug 2023
Post-train Black-box Defense via Bayesian Boundary Correction
Post-train Black-box Defense via Bayesian Boundary Correction
He-Nan Wang
Yunfeng Diao
AAML
36
1
0
29 Jun 2023
SAFARI: Versatile and Efficient Evaluations for Robustness of
  Interpretability
SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability
Wei Huang
Xingyu Zhao
Gao Jin
Xiaowei Huang
AAML
32
29
0
19 Aug 2022
Adversarial Vertex Mixup: Toward Better Adversarially Robust
  Generalization
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
Saehyung Lee
Hyungyu Lee
Sungroh Yoon
AAML
161
113
0
05 Mar 2020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent
  Estimates
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea
Mahdi Haghifam
Gintare Karolina Dziugaite
Ashish Khisti
Daniel M. Roy
FedML
110
146
0
06 Nov 2019
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
2,889
0
15 Sep 2016
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