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Overfitting in adversarially robust deep learning

Overfitting in adversarially robust deep learning

26 February 2020
Leslie Rice
Eric Wong
Zico Kolter
ArXivPDFHTML

Papers citing "Overfitting in adversarially robust deep learning"

50 / 182 papers shown
Title
On the Robustness of Randomized Ensembles to Adversarial Perturbations
On the Robustness of Randomized Ensembles to Adversarial Perturbations
Hassan Dbouk
Naresh R Shanbhag
AAML
23
7
0
02 Feb 2023
Language-Driven Anchors for Zero-Shot Adversarial Robustness
Language-Driven Anchors for Zero-Shot Adversarial Robustness
Xiao-Li Li
Wei Emma Zhang
Yining Liu
Zhan Hu
Bo-Wen Zhang
Xiaolin Hu
34
8
0
30 Jan 2023
Selecting Models based on the Risk of Damage Caused by Adversarial
  Attacks
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
Jona Klemenc
Holger Trittenbach
AAML
24
1
0
28 Jan 2023
A Data-Centric Approach for Improving Adversarial Training Through the
  Lens of Out-of-Distribution Detection
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection
Mohammad Azizmalayeri
Arman Zarei
Alireza Isavand
M. T. Manzuri
M. Rohban
OODD
35
0
0
25 Jan 2023
Data Augmentation Alone Can Improve Adversarial Training
Data Augmentation Alone Can Improve Adversarial Training
Lin Li
Michael W. Spratling
16
50
0
24 Jan 2023
Strong inductive biases provably prevent harmless interpolation
Strong inductive biases provably prevent harmless interpolation
Michael Aerni
Marco Milanta
Konstantin Donhauser
Fanny Yang
35
9
0
18 Jan 2023
Explainability and Robustness of Deep Visual Classification Models
Explainability and Robustness of Deep Visual Classification Models
Jindong Gu
AAML
39
2
0
03 Jan 2023
A Survey of Mix-based Data Augmentation: Taxonomy, Methods,
  Applications, and Explainability
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability
Chengtai Cao
Fan Zhou
Yurou Dai
Jianping Wang
Kunpeng Zhang
AAML
24
28
0
21 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Nikolaos Antoniou
Efthymios Georgiou
Alexandros Potamianos
AAML
29
5
0
15 Dec 2022
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models
Chengzhi Mao
Scott Geng
Junfeng Yang
Xin Eric Wang
Carl Vondrick
VLM
44
59
0
14 Dec 2022
Robust Perception through Equivariance
Robust Perception through Equivariance
Chengzhi Mao
Lingyu Zhang
Abhishek Joshi
Junfeng Yang
Hongya Wang
Carl Vondrick
BDL
AAML
29
7
0
12 Dec 2022
Improving Robust Generalization by Direct PAC-Bayesian Bound
  Minimization
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization
Zifa Wang
Nan Ding
Tomer Levinboim
Xi Chen
Radu Soricut
AAML
35
5
0
22 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A
  Survey
On the Robustness of Explanations of Deep Neural Network Models: A Survey
Amlan Jyoti
Karthik Balaji Ganesh
Manoj Gayala
Nandita Lakshmi Tunuguntla
Sandesh Kamath
V. Balasubramanian
XAI
FAtt
AAML
32
4
0
09 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks
An Adversarial Robustness Perspective on the Topology of Neural Networks
Morgane Goibert
Thomas Ricatte
Elvis Dohmatob
AAML
11
2
0
04 Nov 2022
ARDIR: Improving Robustness using Knowledge Distillation of Internal
  Representation
ARDIR: Improving Robustness using Knowledge Distillation of Internal Representation
Tomokatsu Takahashi
Masanori Yamada
Yuuki Yamanaka
Tomoya Yamashita
20
0
0
01 Nov 2022
Scoring Black-Box Models for Adversarial Robustness
Scoring Black-Box Models for Adversarial Robustness
Jian Vora
Pranay Reddy Samala
33
0
0
31 Oct 2022
Adversarial Purification with the Manifold Hypothesis
Adversarial Purification with the Manifold Hypothesis
Zhaoyuan Yang
Zhiwei Xu
Jing Zhang
Richard I. Hartley
Peter Tu
AAML
24
5
0
26 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz
Tsui-Wei Weng
Gal Mishne
OOD
28
4
0
20 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds
Scaling Adversarial Training to Large Perturbation Bounds
Sravanti Addepalli
Samyak Jain
Gaurang Sriramanan
R. Venkatesh Babu
AAML
33
22
0
18 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from
  Training to Architecture
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Yi Mo
Dongxian Wu
Yifei Wang
Yiwen Guo
Yisen Wang
ViT
45
52
0
14 Oct 2022
Robust Models are less Over-Confident
Robust Models are less Over-Confident
Julia Grabinski
Paul Gavrikov
J. Keuper
M. Keuper
AAML
36
24
0
12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin
  Regularization
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization
Ziquan Liu
Antoni B. Chan
AAML
27
5
0
11 Oct 2022
Towards Out-of-Distribution Adversarial Robustness
Towards Out-of-Distribution Adversarial Robustness
Adam Ibrahim
Charles Guille-Escuret
Ioannis Mitliagkas
Irina Rish
David M. Krueger
P. Bashivan
OOD
31
6
0
06 Oct 2022
Strength-Adaptive Adversarial Training
Strength-Adaptive Adversarial Training
Chaojian Yu
Dawei Zhou
Li Shen
Jun Yu
Bo Han
Biwei Huang
Nannan Wang
Tongliang Liu
OOD
17
2
0
04 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
32
30
0
03 Oct 2022
Automatic Data Augmentation via Invariance-Constrained Learning
Automatic Data Augmentation via Invariance-Constrained Learning
Ignacio Hounie
Luiz F. O. Chamon
Alejandro Ribeiro
23
10
0
29 Sep 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial
  Training
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training
Saehyung Lee
Hyungyu Lee
AAML
29
2
0
27 Sep 2022
Deep Double Descent via Smooth Interpolation
Deep Double Descent via Smooth Interpolation
Matteo Gamba
Erik Englesson
Marten Bjorkman
Hossein Azizpour
63
10
0
21 Sep 2022
A Light Recipe to Train Robust Vision Transformers
A Light Recipe to Train Robust Vision Transformers
Edoardo Debenedetti
Vikash Sehwag
Prateek Mittal
ViT
32
68
0
15 Sep 2022
Saliency Guided Adversarial Training for Learning Generalizable Features
  with Applications to Medical Imaging Classification System
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System
Xin Li
Yao Qiang
Chengyin Li
Sijia Liu
D. Zhu
OOD
MedIm
31
4
0
09 Sep 2022
Bag of Tricks for FGSM Adversarial Training
Bag of Tricks for FGSM Adversarial Training
Zichao Li
Li Liu
Zeyu Wang
Yuyin Zhou
Cihang Xie
AAML
33
6
0
06 Sep 2022
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
Muhammad Hassan
Haifei Guan
Aikaterini Melliou
Yuqi Wang
Qianhui Sun
...
Qi Huang
Jiefu Tan
Qinwang Xing
Peiwu Qin
Dongmei Yu
NAI
41
14
0
31 Jul 2022
Membership Inference Attacks via Adversarial Examples
Membership Inference Attacks via Adversarial Examples
Hamid Jalalzai
Elie Kadoche
Rémi Leluc
Vincent Plassier
AAML
FedML
MIACV
38
7
0
27 Jul 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
35
24
0
22 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers
Towards Efficient Adversarial Training on Vision Transformers
Boxi Wu
Jindong Gu
Zhifeng Li
Deng Cai
Xiaofei He
Wei Liu
ViT
AAML
46
37
0
21 Jul 2022
Holistic Robust Data-Driven Decisions
Holistic Robust Data-Driven Decisions
Amine Bennouna
Bart P. G. Van Parys
Ryan Lucas
OOD
36
21
0
19 Jul 2022
How many perturbations break this model? Evaluating robustness beyond
  adversarial accuracy
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
R. Olivier
Bhiksha Raj
AAML
31
5
0
08 Jul 2022
On the Role of Generalization in Transferability of Adversarial Examples
On the Role of Generalization in Transferability of Adversarial Examples
Yilin Wang
Farzan Farnia
AAML
24
10
0
18 Jun 2022
Landscape Learning for Neural Network Inversion
Landscape Learning for Neural Network Inversion
Ruoshi Liu
Chen-Guang Mao
Purva Tendulkar
Hongya Wang
Carl Vondrick
35
8
0
17 Jun 2022
Analysis and Extensions of Adversarial Training for Video Classification
Analysis and Extensions of Adversarial Training for Video Classification
K. A. Kinfu
René Vidal
AAML
30
13
0
16 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at
  Scale
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Gaoyuan Zhang
Songtao Lu
Yihua Zhang
Xiangyi Chen
Pin-Yu Chen
Quanfu Fan
Lee Martie
L. Horesh
Min-Fong Hong
Sijia Liu
OOD
27
12
0
13 Jun 2022
Towards Understanding Sharpness-Aware Minimization
Towards Understanding Sharpness-Aware Minimization
Maksym Andriushchenko
Nicolas Flammarion
AAML
35
133
0
13 Jun 2022
Wavelet Regularization Benefits Adversarial Training
Wavelet Regularization Benefits Adversarial Training
Jun Yan
Huilin Yin
Xiaoyang Deng
Zi-qin Zhao
Wancheng Ge
Hao Zhang
Gerhard Rigoll
AAML
19
2
0
08 Jun 2022
Building Robust Ensembles via Margin Boosting
Building Robust Ensembles via Margin Boosting
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAML
UQCV
45
15
0
07 Jun 2022
Attack-Agnostic Adversarial Detection
Attack-Agnostic Adversarial Detection
Jiaxin Cheng
Mohamed Hussein
J. Billa
Wael AbdAlmageed
AAML
26
0
0
01 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
22
33
0
30 May 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory
  Prediction
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction
Ruochen Jiao
Xiangguo Liu
Takami Sato
Qi Alfred Chen
Qi Zhu
AAML
40
20
0
27 May 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of
  Expressive Power
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power
Binghui Li
Jikai Jin
Han Zhong
J. Hopcroft
Liwei Wang
OOD
82
27
0
27 May 2022
Squeeze Training for Adversarial Robustness
Squeeze Training for Adversarial Robustness
Qizhang Li
Yiwen Guo
W. Zuo
Hao Chen
OOD
39
9
0
23 May 2022
Robust Representation via Dynamic Feature Aggregation
Robust Representation via Dynamic Feature Aggregation
Haozhe Liu
Haoqin Ji
Yuexiang Li
Nanjun He
Haoqian Wu
Feng Liu
Linlin Shen
Yefeng Zheng
AAML
OOD
32
3
0
16 May 2022
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