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Adversarially Robust Generalization Just Requires More Unlabeled Data

Adversarially Robust Generalization Just Requires More Unlabeled Data

3 June 2019
Runtian Zhai
Tianle Cai
Di He
Chen Dan
Kun He
J. Hopcroft
Liwei Wang
ArXivPDFHTML

Papers citing "Adversarially Robust Generalization Just Requires More Unlabeled Data"

50 / 51 papers shown
Title
Adversarial Prompt Distillation for Vision-Language Models
Adversarial Prompt Distillation for Vision-Language Models
Lin Luo
Xin Wang
Bojia Zi
Shihao Zhao
Xingjun Ma
Yu-Gang Jiang
AAML
VLM
89
2
0
22 Nov 2024
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
Maayan Ehrenberg
Roy Ganz
Nir Rosenfeld
AAML
58
0
0
17 Jun 2024
Better Diffusion Models Further Improve Adversarial Training
Better Diffusion Models Further Improve Adversarial Training
Zekai Wang
Tianyu Pang
Chao Du
Min Lin
Weiwei Liu
Shuicheng Yan
DiffM
28
210
0
09 Feb 2023
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Nikolaos Antoniou
Efthymios Georgiou
Alexandros Potamianos
AAML
31
5
0
15 Dec 2022
Adaptive Self-Training for Object Detection
Adaptive Self-Training for Object Detection
Renaud Vandeghen
Gilles Louppe
Marc Van Droogenbroeck
ObjD
43
7
0
07 Dec 2022
Adversarial Rademacher Complexity of Deep Neural Networks
Adversarial Rademacher Complexity of Deep Neural Networks
Jiancong Xiao
Yanbo Fan
Ruoyu Sun
Zhimin Luo
AAML
22
22
0
27 Nov 2022
Improving Adversarial Robustness with Self-Paced Hard-Class Pair
  Reweighting
Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting
Peng-Fei Hou
Jie Han
Xingyu Li
AAML
OOD
23
11
0
26 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training
Stability Analysis and Generalization Bounds of Adversarial Training
Jiancong Xiao
Yanbo Fan
Ruoyu Sun
Jue Wang
Zhimin Luo
AAML
38
30
0
03 Oct 2022
MaxMatch: Semi-Supervised Learning with Worst-Case Consistency
MaxMatch: Semi-Supervised Learning with Worst-Case Consistency
Yangbangyan Jiang Xiaodan Li
Xiaodan Li
YueFeng Chen
Yuan He
Qianqian Xu
Zhiyong Yang
Xiaochun Cao
Qingming Huang
24
18
0
26 Sep 2022
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
Deepak Maurya
Adarsh Barik
Jean Honorio
OOD
AAML
46
0
0
19 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models
Two Heads are Better than One: Robust Learning Meets Multi-branch Models
Dong Huang
Qi Bu
Yuhao Qing
Haowen Pi
Sen Wang
Heming Cui
OOD
AAML
42
0
0
17 Aug 2022
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for
  Robust Electrocardiogram Prediction
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction
Jiacheng Zhu
Jielin Qiu
Zhuolin Yang
Douglas Weber
M. Rosenberg
Emerson Liu
Bo Li
Ding Zhao
OOD
33
13
0
02 Aug 2022
Decoupled Adversarial Contrastive Learning for Self-supervised
  Adversarial Robustness
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Chaoning Zhang
Kang Zhang
Chenshuang Zhang
Axi Niu
Jiu Feng
Chang D. Yoo
In So Kweon
SSL
40
24
0
22 Jul 2022
Queried Unlabeled Data Improves and Robustifies Class-Incremental
  Learning
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning
Tianlong Chen
Sijia Liu
Shiyu Chang
Lisa Amini
Zhangyang Wang
CLL
31
4
0
15 Jun 2022
Robust Weight Perturbation for Adversarial Training
Robust Weight Perturbation for Adversarial Training
Chaojian Yu
Bo Han
Biwei Huang
Li Shen
Shiming Ge
Bo Du
Tongliang Liu
AAML
27
33
0
30 May 2022
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
54
72
0
26 Mar 2022
Why adversarial training can hurt robust accuracy
Why adversarial training can hurt robust accuracy
Jacob Clarysse
Julia Hörrmann
Fanny Yang
AAML
17
18
0
03 Mar 2022
A Characterization of Semi-Supervised Adversarially-Robust PAC
  Learnability
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability
Idan Attias
Steve Hanneke
Yishay Mansour
35
15
0
11 Feb 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
215
345
0
15 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
34
271
0
09 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated
  Channel Maps
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Muhammad Awais
Fengwei Zhou
Chuanlong Xie
Jiawei Li
Sung-Ho Bae
Zhenguo Li
AAML
43
17
0
09 Nov 2021
When Does Contrastive Learning Preserve Adversarial Robustness from
  Pretraining to Finetuning?
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Lijie Fan
Sijia Liu
Pin-Yu Chen
Gaoyuan Zhang
Chuang Gan
AAML
VLM
22
120
0
01 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
36
294
0
18 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural
  Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
48
100
0
07 Oct 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random
  Forest
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest
Gilad Cohen
Raja Giryes
AAML
45
4
0
16 Sep 2021
Distributionally Robust Learning
Distributionally Robust Learning
Ruidi Chen
I. Paschalidis
OOD
32
65
0
20 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them
Florian Tramèr
AAML
30
65
0
24 Jul 2021
Improving Global Adversarial Robustness Generalization With
  Adversarially Trained GAN
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN
Desheng Wang
Wei-dong Jin
Yunpu Wu
Aamir Khan
GAN
36
8
0
08 Mar 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
36
271
0
02 Mar 2021
Multiplicative Reweighting for Robust Neural Network Optimization
Multiplicative Reweighting for Robust Neural Network Optimization
Noga Bar
Tomer Koren
Raja Giryes
OOD
NoLa
20
9
0
24 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness
Recent Advances in Adversarial Training for Adversarial Robustness
Tao Bai
Jinqi Luo
Jun Zhao
Bihan Wen
Qian Wang
AAML
86
476
0
02 Feb 2021
Robust Pre-Training by Adversarial Contrastive Learning
Robust Pre-Training by Adversarial Contrastive Learning
Ziyu Jiang
Tianlong Chen
Ting-Li Chen
Zhangyang Wang
30
228
0
26 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep
  Learning through Adversarial Robustness
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
39
48
0
19 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded
  Adversarial Examples
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
22
325
0
07 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated
  Gradients
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients
Yifei Huang
Yaodong Yu
Hongyang R. Zhang
Yi Ma
Yuan Yao
AAML
37
26
0
28 Sep 2020
Adversarial Training with Stochastic Weight Average
Adversarial Training with Stochastic Weight Average
Joong-won Hwang
Youngwan Lee
Sungchan Oh
Yuseok Bae
OOD
AAML
31
11
0
21 Sep 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial
  Test Examples
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
S. Goldwasser
Adam Tauman Kalai
Y. Kalai
Omar Montasser
AAML
22
38
0
10 Jul 2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian
  Classification
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
Chen Dan
Yuting Wei
Pradeep Ravikumar
26
45
0
29 Jun 2020
Statistical and Algorithmic Insights for Semi-supervised Learning with
  Self-training
Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
Samet Oymak
Talha Cihad Gulcu
27
20
0
19 Jun 2020
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label
  Classifiers
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers
S. Melacci
Gabriele Ciravegna
Angelo Sotgiu
Ambra Demontis
Battista Biggio
Marco Gori
Fabio Roli
22
14
0
06 Jun 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Tianlong Chen
Sijia Liu
Shiyu Chang
Yu Cheng
Lisa Amini
Zhangyang Wang
AAML
18
246
0
28 Mar 2020
Overfitting in adversarially robust deep learning
Overfitting in adversarially robust deep learning
Leslie Rice
Eric Wong
Zico Kolter
47
788
0
26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help,
  Double Descend, or Hurt Generalization
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization
Yifei Min
Lin Chen
Amin Karbasi
AAML
42
69
0
25 Feb 2020
Black-Box Certification with Randomized Smoothing: A Functional
  Optimization Based Framework
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
Dinghuai Zhang
Mao Ye
Chengyue Gong
Zhanxing Zhu
Qiang Liu
AAML
24
62
0
21 Feb 2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified
  Radius
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
Runtian Zhai
Chen Dan
Di He
Huan Zhang
Boqing Gong
Pradeep Ravikumar
Cho-Jui Hsieh
Liwei Wang
OOD
AAML
27
177
0
08 Jan 2020
Self-training with Noisy Student improves ImageNet classification
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie
Minh-Thang Luong
Eduard H. Hovy
Quoc V. Le
NoLa
88
2,365
0
11 Nov 2019
Nesterov Accelerated Gradient and Scale Invariance for Adversarial
  Attacks
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks
Jiadong Lin
Chuanbiao Song
Kun He
Liwei Wang
J. Hopcroft
AAML
38
555
0
17 Aug 2019
Adversarial Training Can Hurt Generalization
Adversarial Training Can Hurt Generalization
Aditi Raghunathan
Sang Michael Xie
Fanny Yang
John C. Duchi
Percy Liang
24
240
0
14 Jun 2019
Intriguing properties of adversarial training at scale
Intriguing properties of adversarial training at scale
Cihang Xie
Alan Yuille
AAML
13
68
0
10 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data
Robustness to Adversarial Perturbations in Learning from Incomplete Data
Amir Najafi
S. Maeda
Masanori Koyama
Takeru Miyato
OOD
32
129
0
24 May 2019
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