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Evaluating the Robustness of Neural Networks: An Extreme Value Theory
  Approach

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

31 January 2018
Tsui-Wei Weng
Huan Zhang
Pin-Yu Chen
Jinfeng Yi
D. Su
Yupeng Gao
Cho-Jui Hsieh
Luca Daniel
    AAML
ArXivPDFHTML

Papers citing "Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach"

50 / 96 papers shown
Title
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
Jialei Song
Xingquan Zuo
Feiyang Wang
Hai Huang
Tianle Zhang
AAML
136
0
0
16 Apr 2025
A Margin-Maximizing Fine-Grained Ensemble Method
A Margin-Maximizing Fine-Grained Ensemble Method
Jinghui Yuan
Hao Chen
Renwei Luo
Feiping Nie
44
2
0
19 Sep 2024
Layerwise Change of Knowledge in Neural Networks
Layerwise Change of Knowledge in Neural Networks
Xu Cheng
Lei Cheng
Zhaoran Peng
Yang Xu
Tian Han
Quanshi Zhang
KELM
FAtt
35
5
0
13 Sep 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in
  Deep Robust Classifiers
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
Jonas Ngnawé
Sabyasachi Sahoo
Y. Pequignot
Frédéric Precioso
Christian Gagné
AAML
42
0
0
26 Jun 2024
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
Hanlin Gu
W. Ong
Chee Seng Chan
Lixin Fan
MU
39
7
0
23 May 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
30
3
0
12 Apr 2024
Specification Overfitting in Artificial Intelligence
Specification Overfitting in Artificial Intelligence
Benjamin Roth
Pedro Henrique Luz de Araujo
Yuxi Xia
Saskia Kaltenbrunner
Christoph Korab
58
0
0
13 Mar 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar
Swagatam Haldar
Dennis L. Wei
Karthikeyan N. Ramamurthy
FAtt
40
2
0
17 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
31
16
0
02 Feb 2024
How Smooth Is Attention?
How Smooth Is Attention?
Valérie Castin
Pierre Ablin
Gabriel Peyré
AAML
40
9
0
22 Dec 2023
BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense
  with Backdoor Exclusivity Lifting
BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense with Backdoor Exclusivity Lifting
Huming Qiu
Junjie Sun
Mi Zhang
Xudong Pan
Min Yang
AAML
42
4
0
08 Dec 2023
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep
  Neural Networks
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
Yang Wang
B. Dong
Ke Xu
Haiyin Piao
Yufei Ding
Baocai Yin
Xin Yang
AAML
39
3
0
10 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Mahyar Fazlyab
Taha Entesari
Aniket Roy
Ramalingam Chellappa
AAML
16
11
0
29 Sep 2023
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled
  Safety Critical Systems
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems
Saddek Bensalem
Chih-Hong Cheng
Wei Huang
Xiaowei Huang
Changshun Wu
Xingyu Zhao
AAML
27
6
0
20 Jul 2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial
  Robustness
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness
Jovon Craig
Joshua Andle
Theodore S. Nowak
Salimeh Yasaei Sekeh
AAML
47
0
0
07 Jul 2023
Boosting-based Construction of BDDs for Linear Threshold Functions and
  Its Application to Verification of Neural Networks
Boosting-based Construction of BDDs for Linear Threshold Functions and Its Application to Verification of Neural Networks
Yiping Tang
Kohei Hatano
Eiji Takimoto
16
0
0
08 Jun 2023
Decoupled Rationalization with Asymmetric Learning Rates: A Flexible
  Lipschitz Restraint
Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint
Wei Liu
Jun Wang
Yining Qi
Rui Li
Yang Qiu
Yuankai Zhang
Jie Han
Yixiong Zou
47
12
0
23 May 2023
A Survey of Safety and Trustworthiness of Large Language Models through
  the Lens of Verification and Validation
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Xiaowei Huang
Wenjie Ruan
Wei Huang
Gao Jin
Yizhen Dong
...
Sihao Wu
Peipei Xu
Dengyu Wu
André Freitas
Mustafa A. Mustafa
ALM
45
83
0
19 May 2023
Uncertainty Estimation and Out-of-Distribution Detection for Deep
  Learning-Based Image Reconstruction using the Local Lipschitz
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz
D. Bhutto
Bo Zhu
J. Liu
Neha Koonjoo
H. Li
Bruce Rosen
M. Rosen
UQCV
OOD
15
2
0
12 May 2023
Machine Learning with Requirements: a Manifesto
Machine Learning with Requirements: a Manifesto
Eleonora Giunchiglia
F. Imrie
M. Schaar
Thomas Lukasiewicz
AI4TS
OffRL
VLM
40
5
0
07 Apr 2023
POLAR-Express: Efficient and Precise Formal Reachability Analysis of
  Neural-Network Controlled Systems
POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems
Yixuan Wang
Weichao Zhou
Jiameng Fan
Zhilu Wang
Jiajun Li
Xin Chen
Chao Huang
Wenchao Li
Qi Zhu
41
15
0
31 Mar 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust
  Out-Of-Distribution Detection
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection
Nicola Franco
Daniel Korth
J. Lorenz
Karsten Roscher
Stephan Guennemann
30
5
0
27 Mar 2023
FederatedTrust: A Solution for Trustworthy Federated Learning
FederatedTrust: A Solution for Trustworthy Federated Learning
Pedro Miguel Sánchez Sánchez
Alberto Huertas Celdrán
Ning Xie
Gérome Bovet
Gregorio Martínez Pérez
Burkhard Stiller
36
21
0
20 Feb 2023
ComplAI: Theory of A Unified Framework for Multi-factor Assessment of
  Black-Box Supervised Machine Learning Models
ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models
Arkadipta De
Satya Swaroop Gudipudi
Sourab Panchanan
M. Desarkar
FaML
13
0
0
30 Dec 2022
Deep Fake Detection, Deterrence and Response: Challenges and
  Opportunities
Deep Fake Detection, Deterrence and Response: Challenges and Opportunities
Amin Azmoodeh
Ali Dehghantanha
45
2
0
26 Nov 2022
Robustness in deep learning: The good (width), the bad (depth), and the
  ugly (initialization)
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)
Zhenyu Zhu
Fanghui Liu
Grigorios G. Chrysos
V. Cevher
39
19
0
15 Sep 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under
  Unseen Distribution Shifts
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang
Junyuan Hong
Jiayu Zhou
Zhangyang Wang
OOD
60
11
0
04 Jul 2022
Distributional Gaussian Processes Layers for Out-of-Distribution
  Detection
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
29
0
0
27 Jun 2022
Safe Output Feedback Motion Planning from Images via Learned Perception
  Modules and Contraction Theory
Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory
Glen Chou
N. Ozay
Dmitry Berenson
19
22
0
14 Jun 2022
Hierarchical Distribution-Aware Testing of Deep Learning
Hierarchical Distribution-Aware Testing of Deep Learning
Wei Huang
Xingyu Zhao
Alec Banks
V. Cox
Xiaowei Huang
OOD
AAML
39
10
0
17 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Xingliang Yuan
Shirui Pan
Hanghang Tong
Jian Pei
45
104
0
16 May 2022
Discovering and Explaining the Representation Bottleneck of Graph Neural
  Networks from Multi-order Interactions
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions
Fang Wu
Siyuan Li
Lirong Wu
Dragomir R. Radev
Stan Z. Li
27
2
0
15 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via
  Distance-Awareness
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
J. Liu
Shreyas Padhy
Jie Jessie Ren
Zi Lin
Yeming Wen
Ghassen Jerfel
Zachary Nado
Jasper Snoek
Dustin Tran
Balaji Lakshminarayanan
UQCV
BDL
26
48
0
01 May 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization
  Perspective
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
26
33
0
27 Mar 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
49
72
0
26 Mar 2022
A Domain-Theoretic Framework for Robustness Analysis of Neural Networks
A Domain-Theoretic Framework for Robustness Analysis of Neural Networks
Can Zhou
R. A. Shaikh
Yiran Li
Amin Farjudian
OOD
38
4
0
01 Mar 2022
Excitement Surfeited Turns to Errors: Deep Learning Testing Framework
  Based on Excitable Neurons
Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable Neurons
Haibo Jin
Ruoxi Chen
Haibin Zheng
Jinyin Chen
Yao Cheng
Yue Yu
Xianglong Liu
AAML
28
6
0
12 Feb 2022
On the Impact of Hard Adversarial Instances on Overfitting in
  Adversarial Training
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
23
13
0
14 Dec 2021
Discovering and Explaining the Representation Bottleneck of DNNs
Discovering and Explaining the Representation Bottleneck of DNNs
Huiqi Deng
Qihan Ren
Hao Zhang
Quanshi Zhang
39
59
0
11 Nov 2021
Visualizing the Emergence of Intermediate Visual Patterns in DNNs
Visualizing the Emergence of Intermediate Visual Patterns in DNNs
Mingjie Li
Shaobo Wang
Quanshi Zhang
44
11
0
05 Nov 2021
ε-weakened Robustness of Deep Neural Networks
ε-weakened Robustness of Deep Neural Networks
Pei Huang
Yuting Yang
Minghao Liu
Fuqi Jia
Feifei Ma
Jian Zhang
AAML
27
18
0
29 Oct 2021
AugMax: Adversarial Composition of Random Augmentations for Robust
  Training
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Haotao Wang
Chaowei Xiao
Jean Kossaifi
Zhiding Yu
Anima Anandkumar
Zhangyang Wang
27
106
0
26 Oct 2021
Characterizing Learning Dynamics of Deep Neural Networks via Complex
  Networks
Characterizing Learning Dynamics of Deep Neural Networks via Complex Networks
Emanuele La Malfa
G. Malfa
Giuseppe Nicosia
Vito Latora
30
10
0
06 Oct 2021
Trustworthy AI: From Principles to Practices
Trustworthy AI: From Principles to Practices
Bo-wen Li
Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
119
356
0
04 Oct 2021
On the regularized risk of distributionally robust learning over deep
  neural networks
On the regularized risk of distributionally robust learning over deep neural networks
Camilo A. Garcia Trillos
Nicolas García Trillos
OOD
45
10
0
13 Sep 2021
Neural Architecture Dilation for Adversarial Robustness
Neural Architecture Dilation for Adversarial Robustness
Yanxi Li
Zhaohui Yang
Yunhe Wang
Chang Xu
AAML
38
23
0
16 Aug 2021
Provable Lipschitz Certification for Generative Models
Provable Lipschitz Certification for Generative Models
Matt Jordan
A. Dimakis
22
14
0
06 Jul 2021
Model Error Propagation via Learned Contraction Metrics for Safe
  Feedback Motion Planning of Unknown Systems
Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown Systems
Glen Chou
N. Ozay
Dmitry Berenson
32
25
0
18 Apr 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 Wang
Meng Zhou
Jie Shi
Quanshi Zhang
AAML
72
22
0
12 Mar 2021
Non-Singular Adversarial Robustness of Neural Networks
Non-Singular Adversarial Robustness of Neural Networks
Yu-Lin Tsai
Chia-Yi Hsu
Chia-Mu Yu
Pin-Yu Chen
AAML
OOD
14
5
0
23 Feb 2021
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