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Learnable Boundary Guided Adversarial Training

Learnable Boundary Guided Adversarial Training

23 November 2020
Jiequan Cui
Shu-Lin Liu
Liwei Wang
Jiaya Jia
    OOD
    AAML
ArXivPDFHTML

Papers citing "Learnable Boundary Guided Adversarial Training"

36 / 86 papers shown
Title
Class-Level Logit Perturbation
Class-Level Logit Perturbation
Mengyang Li
Fengguang Su
O. Wu
Tianjin University
AAML
29
3
0
13 Sep 2022
Revisiting Outer Optimization in Adversarial Training
Revisiting Outer Optimization in Adversarial Training
Ali Dabouei
Fariborz Taherkhani
Sobhan Soleymani
Nasser M. Nasrabadi
AAML
17
4
0
02 Sep 2022
A Multi-objective Memetic Algorithm for Auto Adversarial Attack
  Optimization Design
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design
Jialiang Sun
Wen Yao
Tingsong Jiang
Xiaoqian Chen
AAML
18
0
0
15 Aug 2022
Aries: Efficient Testing of Deep Neural Networks via Labeling-Free
  Accuracy Estimation
Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation
Qiang Hu
Yuejun Guo
Xiaofei Xie
Maxime Cordy
Lei Ma
Mike Papadakis
Yves Le Traon
AAML
12
17
0
22 Jul 2022
Towards the Desirable Decision Boundary by Moderate-Margin Adversarial
  Training
Towards the Desirable Decision Boundary by Moderate-Margin Adversarial Training
Xiaoyu Liang
Yaguan Qian
Jianchang Huang
Xiang Ling
Bin Wang
Chunming Wu
Wassim Swaileh
AAML
20
2
0
16 Jul 2022
Diversified Adversarial Attacks based on Conjugate Gradient Method
Diversified Adversarial Attacks based on Conjugate Gradient Method
Keiichiro Yamamura
Haruki Sato
Nariaki Tateiwa
Nozomi Hata
Toru Mitsutake
Issa Oe
Hiroki Ishikura
Katsuki Fujisawa
AAML
14
14
0
20 Jun 2022
Vanilla Feature Distillation for Improving the Accuracy-Robustness
  Trade-Off in Adversarial Training
Vanilla Feature Distillation for Improving the Accuracy-Robustness Trade-Off in Adversarial Training
Guodong Cao
Zhibo Wang
Xiaowei Dong
Zhifei Zhang
Hengchang Guo
Zhan Qin
Kui Ren
AAML
22
1
0
05 Jun 2022
FACM: Intermediate Layer Still Retain Effective Features against
  Adversarial Examples
FACM: Intermediate Layer Still Retain Effective Features against Adversarial Examples
Xiangyuan Yang
Jie Lin
Hanlin Zhang
Xinyu Yang
Peng Zhao
AAML
34
0
0
02 Jun 2022
Rethinking Classifier and Adversarial Attack
Rethinking Classifier and Adversarial Attack
Youhuan Yang
Lei Sun
Leyu Dai
Song Guo
Xiuqing Mao
Xiaoqin Wang
Bayi Xu
AAML
19
0
0
04 May 2022
CE-based white-box adversarial attacks will not work using super-fitting
CE-based white-box adversarial attacks will not work using super-fitting
Youhuan Yang
Lei Sun
Leyu Dai
Song Guo
Xiuqing Mao
Xiaoqin Wang
Bayi Xu
AAML
24
0
0
04 May 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
CNN Filter DB: An Empirical Investigation of Trained Convolutional
  Filters
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters
Paul Gavrikov
J. Keuper
AAML
16
31
0
29 Mar 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
36
131
0
13 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights
Enhancing Adversarial Training with Second-Order Statistics of Weights
Gao Jin
Xinping Yi
Wei Huang
S. Schewe
Xiaowei Huang
AAML
12
46
0
11 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
Ye Liu
Yaya Cheng
Lianli Gao
Xianglong Liu
Qilong Zhang
Jingkuan Song
AAML
30
56
0
10 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for
  Adversarial Training
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Tu Bui
Trung Le
Quan Hung Tran
He Zhao
Dinh Q. Phung
AAML
OOD
26
42
0
27 Feb 2022
Improving Robustness by Enhancing Weak Subnets
Improving Robustness by Enhancing Weak Subnets
Yong Guo
David Stutz
Bernt Schiele
AAML
14
15
0
30 Jan 2022
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive
  Framework for Improving Adversarial Robustness
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness
Jia-Li Yin
Lehui Xie
Wanqing Zhu
Ximeng Liu
Bo-Hao Chen
TTA
AAML
11
3
0
01 Dec 2021
Data Augmentation Can Improve Robustness
Data Augmentation Can Improve Robustness
Sylvestre-Alvise Rebuffi
Sven Gowal
D. A. Calian
Florian Stimberg
Olivia Wiles
Timothy A. Mann
AAML
17
267
0
09 Nov 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss
  Function Search
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search
Pengfei Xia
Ziqiang Li
Bin Li
AAML
32
3
0
09 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training
LTD: Low Temperature Distillation for Robust Adversarial Training
Erh-Chung Chen
Che-Rung Lee
AAML
19
26
0
03 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based
  Adversarial Attacks
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Maksym Yatsura
J. H. Metzen
Matthias Hein
OOD
16
14
0
02 Nov 2021
Improving Robustness using Generated Data
Improving Robustness using Generated Data
Sven Gowal
Sylvestre-Alvise Rebuffi
Olivia Wiles
Florian Stimberg
D. A. Calian
Timothy A. Mann
20
292
0
18 Oct 2021
Adversarial Visual Robustness by Causal Intervention
Adversarial Visual Robustness by Causal Intervention
Kaihua Tang
Ming Tao
Hanwang Zhang
CML
AAML
19
21
0
17 Jun 2021
Attacking Adversarial Attacks as A Defense
Attacking Adversarial Attacks as A Defense
Boxi Wu
Heng Pan
Li Shen
Jindong Gu
Shuai Zhao
Zhifeng Li
Deng Cai
Xiaofei He
Wei Liu
AAML
20
31
0
09 Jun 2021
Exploring Misclassifications of Robust Neural Networks to Enhance
  Adversarial Attacks
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks
Leo Schwinn
René Raab
A. Nguyen
Dario Zanca
Bjoern M. Eskofier
AAML
14
57
0
21 May 2021
Dual Head Adversarial Training
Dual Head Adversarial Training
Yujing Jiang
Xingjun Ma
S. Erfani
James Bailey
AAML
19
4
0
21 Apr 2021
Robust Learning Meets Generative Models: Can Proxy Distributions Improve
  Adversarial Robustness?
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
Vikash Sehwag
Saeed Mahloujifar
Tinashe Handina
Sihui Dai
Chong Xiang
M. Chiang
Prateek Mittal
OOD
39
126
0
19 Apr 2021
Distilling Knowledge via Knowledge Review
Distilling Knowledge via Knowledge Review
Pengguang Chen
Shu-Lin Liu
Hengshuang Zhao
Jiaya Jia
147
419
0
19 Apr 2021
Fixing Data Augmentation to Improve Adversarial Robustness
Fixing Data Augmentation to Improve Adversarial Robustness
Sylvestre-Alvise Rebuffi
Sven Gowal
D. A. Calian
Florian Stimberg
Olivia Wiles
Timothy A. Mann
AAML
25
268
0
02 Mar 2021
Understanding and Achieving Efficient Robustness with Adversarial
  Supervised Contrastive Learning
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning
Anh-Vu Bui
Trung Le
He Zhao
Paul Montague
S. Çamtepe
Dinh Q. Phung
AAML
11
14
0
25 Jan 2021
Towards Robust Neural Networks via Orthogonal Diversity
Towards Robust Neural Networks via Orthogonal Diversity
Kun Fang
Qinghua Tao
Yingwen Wu
Tao Li
Jia Cai
Feipeng Cai
Xiaolin Huang
Jie-jin Yang
AAML
28
8
0
23 Oct 2020
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
217
675
0
19 Oct 2020
Stylized Adversarial Defense
Stylized Adversarial Defense
Muzammal Naseer
Salman Khan
Munawar Hayat
F. Khan
Fatih Porikli
GAN
AAML
20
16
0
29 Jul 2020
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
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
252
5,833
0
08 Jul 2016
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