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1610.04563
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Are Accuracy and Robustness Correlated?
International Conference on Machine Learning and Applications (ICMLA), 2016
14 October 2016
Andras Rozsa
Manuel Günther
Terrance E. Boult
AAML
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Papers citing
"Are Accuracy and Robustness Correlated?"
33 / 33 papers shown
Robust-IR @ SIGIR 2025: The First Workshop on Robust Information Retrieval
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2025
Yu-an Liu
Haya Nachimovsky
Ruqing Zhang
Oren Kurland
Jiafeng Guo
Moshe Tennenholtz
OffRL
159
1
0
24 Mar 2025
On the uncertainty principle of neural networks
iScience (iScience), 2022
Jun-Jie Zhang
Dong-xiao Zhang
Jian-Nan Chen
L. Pang
Deyu Meng
470
6
0
17 Jan 2025
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
ACM Computing Surveys (ACM CSUR), 2024
Firas Bayram
Bestoun S. Ahmed
OOD
192
17
0
28 Oct 2024
Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of Conjugate Variables in System Attacks
Jun-Jie Zhang
Deyu Meng
AAML
251
4
0
16 Feb 2024
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
International Conference on Learning Representations (ICLR), 2023
Peiyan Zhang
Hao Liu
Chaozhuo Li
Xing Xie
Sunghun Kim
Haohan Wang
VLM
OOD
349
8
0
21 Aug 2023
Causality-Aided Trade-off Analysis for Machine Learning Fairness
International Conference on Automated Software Engineering (ASE), 2023
Zhenlan Ji
Pingchuan Ma
Shuai Wang
Yanhui Li
FaML
414
15
0
22 May 2023
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification
Journal of machine learning research (JMLR), 2022
Natalie Frank
Jonathan Niles-Weed
AAML
339
17
0
18 Jun 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
International Conference on Machine Learning (ICML), 2022
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
417
151
0
21 Feb 2022
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
Knowledge Discovery and Data Mining (KDD), 2021
Kailun Wu
Zhangming Chan
Weijie Bian
Lejian Ren
Shiming Xiang
Shuguang Han
Hongbo Deng
Bo Zheng
299
13
0
21 Dec 2021
Semantic Perturbations with Normalizing Flows for Improved Generalization
Oğuz Kaan Yüksel
Sebastian U. Stich
Martin Jaggi
Tatjana Chavdarova
AAML
198
12
0
18 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Lin Wang
Navid Kardan
M. Shah
AAML
489
298
0
01 Aug 2021
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective
Lina Wang
Xingshu Chen
Yulong Wang
Yawei Yue
Yi Zhu
Xuemei Zeng
Wei Wang
AAML
114
0
0
18 Jun 2021
Robustness and Transferability of Universal Attacks on Compressed Models
Alberto G. Matachana
Kenneth T. Co
Luis Muñoz-González
David Martínez
Emil C. Lupu
AAML
176
11
0
10 Dec 2020
Robustified Domain Adaptation
Jiajin Zhang
Hanqing Chao
Pingkun Yan
143
4
0
18 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks
Tao Bai
Jinqi Luo
Jun Zhao
AAML
243
9
0
03 Nov 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey
ACM Computing Surveys (ACM CSUR), 2020
A. Serban
E. Poll
Joost Visser
AAML
420
80
0
07 Aug 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
Computer Vision and Pattern Recognition (CVPR), 2020
Ahmadreza Jeddi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
OOD
AAML
378
72
0
02 Mar 2020
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2019
Stacey Truex
Ling Liu
Mehmet Emre Gursoy
Wenqi Wei
Lei Yu
MIACV
159
56
0
21 Nov 2019
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
E. Balda
Arash Behboodi
Niklas Koep
R. Mathar
AAML
178
9
0
03 Jun 2019
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
Computer Vision and Pattern Recognition (CVPR), 2019
Haohan Wang
Xindi Wu
Pengcheng Yin
Eric Xing
402
629
0
28 May 2019
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks
P. Langenberg
E. Balda
Arash Behboodi
R. Mathar
226
15
0
29 Jan 2019
The Limitations of Model Uncertainty in Adversarial Settings
Kathrin Grosse
David Pfaff
M. Smith
Michael Backes
AAML
120
39
0
06 Dec 2018
Disentangling Adversarial Robustness and Generalization
David Stutz
Matthias Hein
Bernt Schiele
AAML
OOD
653
305
0
03 Dec 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon
A. Serban
E. Poll
Joost Visser
SILM
AAML
256
50
0
02 Oct 2018
Adversarial Examples: Opportunities and Challenges
Jiliang Zhang
Chen Li
AAML
241
270
0
13 Sep 2018
Detection based Defense against Adversarial Examples from the Steganalysis Point of View
Jiayang Liu
Weiming Zhang
Yiwei Zhang
Dongdong Hou
Yujia Liu
Hongyue Zha
Nenghai Yu
AAML
267
107
0
21 Jun 2018
Como funciona o Deep Learning
M. Ponti
G. B. P. D. Costa
108
14
0
20 Jun 2018
Adversarial Meta-Learning
Chengxiang Yin
Jian Tang
Zhiyuan Xu
Yanzhi Wang
197
44
0
08 Jun 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Lin Wang
AAML
519
1,997
0
02 Jan 2018
How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models
Kathrin Grosse
David Pfaff
M. Smith
Michael Backes
AAML
255
9
0
17 Nov 2017
Adversarial Frontier Stitching for Remote Neural Network Watermarking
Erwan Le Merrer
P. Pérez
Gilles Trédan
MLAU
AAML
189
378
0
06 Nov 2017
On Detecting Adversarial Perturbations
International Conference on Learning Representations (ICLR), 2017
J. H. Metzen
Tim Genewein
Volker Fischer
Bastian Bischoff
AAML
331
1,009
0
14 Feb 2017
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
873
3,328
0
04 Nov 2016
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