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Theoretically Principled Trade-off between Robustness and Accuracy

Theoretically Principled Trade-off between Robustness and Accuracy

24 January 2019
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
ArXivPDFHTML

Papers citing "Theoretically Principled Trade-off between Robustness and Accuracy"

50 / 595 papers shown
Title
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
Built-in Elastic Transformations for Improved Robustness
Built-in Elastic Transformations for Improved Robustness
Sadaf Gulshad
Ivan Sosnovik
A. Smeulders
AAML
22
1
0
20 Jul 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang
Eunjung Lee
Wonjong Rhee
AAML
167
15
0
14 Jul 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
104
196
0
12 Jul 2021
Towards Robust General Medical Image Segmentation
Towards Robust General Medical Image Segmentation
Laura Alexandra Daza
Juan C. Pérez
Pablo Arbelaez
OOD
31
25
0
09 Jul 2021
Predicting Disease Progress with Imprecise Lab Test Results
Predicting Disease Progress with Imprecise Lab Test Results
Mei Wang
Jianwen Su
Zhi-kai Lin
10
0
0
08 Jul 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via
  Gradient Diversity Regularization
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization
Sungyoon Lee
Hoki Kim
Jaewook Lee
AAML
35
52
0
06 Jul 2021
DVS-Attacks: Adversarial Attacks on Dynamic Vision Sensors for Spiking
  Neural Networks
DVS-Attacks: Adversarial Attacks on Dynamic Vision Sensors for Spiking Neural Networks
Alberto Marchisio
Giacomo Pira
Maurizio Martina
Guido Masera
Mohamed Bennai
AAML
36
30
0
01 Jul 2021
The Values Encoded in Machine Learning Research
The Values Encoded in Machine Learning Research
Abeba Birhane
Pratyusha Kalluri
Dallas Card
William Agnew
Ravit Dotan
Michelle Bao
41
275
0
29 Jun 2021
Attack Transferability Characterization for Adversarially Robust
  Multi-label Classification
Attack Transferability Characterization for Adversarially Robust Multi-label Classification
Zhuo Yang
Yufei Han
Xiangliang Zhang
AAML
23
4
0
29 Jun 2021
Can contrastive learning avoid shortcut solutions?
Can contrastive learning avoid shortcut solutions?
Joshua Robinson
Li Sun
Ke Yu
Kayhan Batmanghelich
Stefanie Jegelka
S. Sra
SSL
19
142
0
21 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations
Adversarial Training Helps Transfer Learning via Better Representations
Zhun Deng
Linjun Zhang
Kailas Vodrahalli
Kenji Kawaguchi
James Zou
GAN
36
53
0
18 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization
Adversarial Robustness via Fisher-Rao Regularization
Marine Picot
Francisco Messina
Malik Boudiaf
Fabrice Labeau
Ismail Ben Ayed
Pablo Piantanida
AAML
31
23
0
12 Jun 2021
Adversarial purification with Score-based generative models
Adversarial purification with Score-based generative models
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
25
153
0
11 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and Primer
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zhangyang Wang
J. Yadawa
26
31
0
09 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of
  Noisy Labels
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels
Jingfeng Zhang
Xilie Xu
Bo Han
Tongliang Liu
Gang Niu
Li-zhen Cui
Masashi Sugiyama
NoLa
AAML
23
9
0
31 May 2021
Analysis and Applications of Class-wise Robustness in Adversarial
  Training
Analysis and Applications of Class-wise Robustness in Adversarial Training
Qi Tian
Kun Kuang
Ke Jiang
Fei Wu
Yisen Wang
AAML
20
46
0
29 May 2021
Demotivate adversarial defense in remote sensing
Demotivate adversarial defense in remote sensing
Adrien Chan-Hon-Tong
Gaston Lenczner
A. Plyer
AAML
30
5
0
28 May 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
60
0
21 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial
  Attacks
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
Dequan Wang
An Ju
Evan Shelhamer
David Wagner
Trevor Darrell
AAML
26
27
0
18 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation
Sparta: Spatially Attentive and Adversarially Robust Activation
Qing Guo
Felix Juefei Xu
Changqing Zhou
Wei Feng
Yang Liu
Song Wang
AAML
33
4
0
18 May 2021
This Looks Like That... Does it? Shortcomings of Latent Space Prototype
  Interpretability in Deep Networks
This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks
Adrian Hoffmann
Claudio Fanconi
Rahul Rade
Jonas Köhler
22
63
0
05 May 2021
Impact of Spatial Frequency Based Constraints on Adversarial Robustness
Impact of Spatial Frequency Based Constraints on Adversarial Robustness
Rémi Bernhard
Pierre-Alain Moëllic
Martial Mermillod
Yannick Bourrier
Romain Cohendet
M. Solinas
M. Reyboz
AAML
30
17
0
26 Apr 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
Yunrui Yu
Xitong Gao
Chengzhong Xu
AAML
FedML
33
44
0
19 Apr 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure
  DNN Accelerators
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators
David Stutz
Nandhini Chandramoorthy
Matthias Hein
Bernt Schiele
AAML
MQ
24
18
0
16 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima
Relating Adversarially Robust Generalization to Flat Minima
David Stutz
Matthias Hein
Bernt Schiele
OOD
38
65
0
09 Apr 2021
Universal Adversarial Training with Class-Wise Perturbations
Universal Adversarial Training with Class-Wise Perturbations
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
AAML
25
26
0
07 Apr 2021
Adversarial Robustness under Long-Tailed Distribution
Adversarial Robustness under Long-Tailed Distribution
Tong Wu
Ziwei Liu
Qingqiu Huang
Yu Wang
Dahua Lin
21
76
0
06 Apr 2021
Robust Adversarial Classification via Abstaining
Robust Adversarial Classification via Abstaining
Abed AlRahman Al Makdah
Vaibhav Katewa
Fabio Pasqualetti
21
0
0
06 Apr 2021
Adaptive Clustering of Robust Semantic Representations for Adversarial
  Image Purification
Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification
S. Silva
Arun Das
I. Scarff
Peyman Najafirad
AAML
20
1
0
05 Apr 2021
Neural Network Robustness as a Verification Property: A Principled Case
  Study
Neural Network Robustness as a Verification Property: A Principled Case Study
Marco Casadio
Ekaterina Komendantskaya
M. Daggitt
Wen Kokke
Guy Katz
Guy Amir
Idan Refaeli
OOD
AAML
19
39
0
03 Apr 2021
On the Adversarial Robustness of Vision Transformers
On the Adversarial Robustness of Vision Transformers
Rulin Shao
Zhouxing Shi
Jinfeng Yi
Pin-Yu Chen
Cho-Jui Hsieh
ViT
33
138
0
29 Mar 2021
Enhancing the Transferability of Adversarial Attacks through Variance
  Tuning
Enhancing the Transferability of Adversarial Attacks through Variance Tuning
Xiaosen Wang
Kun He
AAML
45
379
0
29 Mar 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection
LiBRe: A Practical Bayesian Approach to Adversarial Detection
Zhijie Deng
Xiao Yang
Shizhen Xu
Hang Su
Jun Zhu
BDL
AAML
25
61
0
27 Mar 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for
  Enhanced Adversarial Robustness
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
27
4
0
27 Mar 2021
Unsupervised Robust Domain Adaptation without Source Data
Unsupervised Robust Domain Adaptation without Source Data
Peshal Agarwal
D. Paudel
Jan-Nico Zaech
Luc Van Gool
OOD
TTA
29
27
0
26 Mar 2021
Combating Adversaries with Anti-Adversaries
Combating Adversaries with Anti-Adversaries
Motasem Alfarra
Juan C. Pérez
Ali K. Thabet
Adel Bibi
Philip Torr
Guohao Li
AAML
34
27
0
26 Mar 2021
Adversarial Attacks are Reversible with Natural Supervision
Adversarial Attacks are Reversible with Natural Supervision
Chengzhi Mao
Mia Chiquer
Hao Wang
Junfeng Yang
Carl Vondrick
BDL
AAML
21
55
0
26 Mar 2021
Robust and Accurate Object Detection via Adversarial Learning
Robust and Accurate Object Detection via Adversarial Learning
Xiangning Chen
Cihang Xie
Mingxing Tan
Li Zhang
Cho-Jui Hsieh
Boqing Gong
AAML
34
72
0
23 Mar 2021
Adversarially Optimized Mixup for Robust Classification
Adversarially Optimized Mixup for Robust Classification
Jason Bunk
Srinjoy Chattopadhyay
B. S. Manjunath
S. Chandrasekaran
AAML
30
8
0
22 Mar 2021
Boosting Adversarial Transferability through Enhanced Momentum
Boosting Adversarial Transferability through Enhanced Momentum
Xiaosen Wang
Jiadong Lin
Han Hu
Jingdong Wang
Kun He
AAML
14
76
0
19 Mar 2021
Adversarial Training is Not Ready for Robot Learning
Adversarial Training is Not Ready for Robot Learning
Mathias Lechner
Ramin Hasani
Radu Grosu
Daniela Rus
T. Henzinger
AAML
38
34
0
15 Mar 2021
Learning Defense Transformers for Counterattacking Adversarial Examples
Learning Defense Transformers for Counterattacking Adversarial Examples
Jincheng Li
Jingyun Liang
Yifan Zhang
Jian Chen
Mingkui Tan
AAML
37
2
0
13 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness
A Unified Game-Theoretic Interpretation of Adversarial Robustness
Jie Ren
Die Zhang
Yisen Wang
Lu Chen
Zhanpeng Zhou
...
Xu Cheng
Xin Eric Wang
Meng Zhou
Jie Shi
Quanshi Zhang
AAML
72
22
0
12 Mar 2021
Consistency Regularization for Adversarial Robustness
Consistency Regularization for Adversarial Robustness
Jihoon Tack
Sihyun Yu
Jongheon Jeong
Minseon Kim
Sung Ju Hwang
Jinwoo Shin
AAML
41
57
0
08 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by
  Adversarial Attack
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack
Mengting Xu
Tao Zhang
Zhongnian Li
Mingxia Liu
Daoqiang Zhang
AAML
OOD
MedIm
33
41
0
05 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Fu Lee Wang
Yanghao Zhang
Yanbin Zheng
Wenjie Ruan
31
1
0
04 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
A Multiclass Boosting Framework for Achieving Fast and Provable
  Adversarial Robustness
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness
Jacob D. Abernethy
Pranjal Awasthi
Satyen Kale
AAML
27
6
0
01 Mar 2021
Multiplicative Reweighting for Robust Neural Network Optimization
Multiplicative Reweighting for Robust Neural Network Optimization
Noga Bar
Tomer Koren
Raja Giryes
OOD
NoLa
18
9
0
24 Feb 2021
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