Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1906.00555
Cited By
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
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Adversarially Robust Generalization Just Requires More Unlabeled Data"
50 / 51 papers shown
Title
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
Maayan Ehrenberg
Roy Ganz
Nir Rosenfeld
AAML
58
0
0
17 Jun 2024
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
Nikolaos Antoniou
Efthymios Georgiou
Alexandros Potamianos
AAML
31
5
0
15 Dec 2022
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
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
Peng-Fei Hou
Jie Han
Xingyu Li
AAML
OOD
23
11
0
26 Oct 2022
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
Yangbangyan Jiang Xiaodan Li
Xiaodan Li
YueFeng Chen
Yuan He
Qianqian Xu
Zhiyong Yang
Xiaochun Cao
Qingming Huang
21
18
0
26 Sep 2022
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
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
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
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
Tianlong Chen
Sijia Liu
Shiyu Chang
Lisa Amini
Zhangyang Wang
CLL
28
4
0
15 Jun 2022
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
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
Jacob Clarysse
Julia Hörrmann
Fanny Yang
AAML
17
18
0
03 Mar 2022
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
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
215
345
0
15 Dec 2021
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
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?
Lijie Fan
Sijia Liu
Pin-Yu Chen
Gaoyuan Zhang
Chuang Gan
AAML
VLM
22
120
0
01 Nov 2021
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
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
Gilad Cohen
Raja Giryes
AAML
45
4
0
16 Sep 2021
Distributionally Robust Learning
Ruidi Chen
I. Paschalidis
OOD
32
65
0
20 Aug 2021
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
Desheng Wang
Wei-dong Jin
Yunpu Wu
Aamir Khan
GAN
36
8
0
08 Mar 2021
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
Noga Bar
Tomer Koren
Raja Giryes
OOD
NoLa
18
9
0
24 Feb 2021
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
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
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
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
Yifei Huang
Yaodong Yu
Hongyang R. Zhang
Yi Ma
Yuan Yao
AAML
37
26
0
28 Sep 2020
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
S. Goldwasser
Adam Tauman Kalai
Y. Kalai
Omar Montasser
AAML
22
38
0
10 Jul 2020
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
Samet Oymak
Talha Cihad Gulcu
27
20
0
19 Jun 2020
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
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
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
Yifei Min
Lin Chen
Amin Karbasi
AAML
39
69
0
25 Feb 2020
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
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
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
Jiadong Lin
Chuanbiao Song
Kun He
Liwei Wang
J. Hopcroft
AAML
38
555
0
17 Aug 2019
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
Cihang Xie
Alan Yuille
AAML
13
68
0
10 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data
Amir Najafi
S. Maeda
Masanori Koyama
Takeru Miyato
OOD
32
129
0
24 May 2019
1
2
Next