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2012.08723
Cited By
Exacerbating Algorithmic Bias through Fairness Attacks
AAAI Conference on Artificial Intelligence (AAAI), 2020
16 December 2020
Ninareh Mehrabi
Muhammad Naveed
Fred Morstatter
Aram Galstyan
AAML
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Papers citing
"Exacerbating Algorithmic Bias through Fairness Attacks"
42 / 42 papers shown
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization
Yucong Dai
Jie Ji
Xiaolong Ma
Yongkai Wu
219
0
0
29 Mar 2025
Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2025
Huan Tian
Guangsheng Zhang
Bo Liu
Tianqing Zhu
Ming Ding
Wanlei Zhou
444
2
0
08 Mar 2025
BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Jiaqi Xue
Qian Lou
Mengxin Zheng
239
3
0
23 Oct 2024
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning
Jiashi Gao
Ziwei Wang
Xiangyu Zhao
Xinming Shi
Xin Yao
Xuetao Wei
395
2
0
09 Oct 2024
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning
International Joint Conference on Artificial Intelligence (IJCAI), 2024
Syed Irfan Ali Meerza
Jian-Dong Liu
293
6
0
02 Oct 2024
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
Gianmario Voria
Giulia Sellitto
Carmine Ferrara
Francesco Abate
A. Lucia
F. Ferrucci
Gemma Catolino
Fabio Palomba
FaML
329
5
0
29 Aug 2024
LayerMatch: Do Pseudo-labels Benefit All Layers?
Chaoqi Liang
Guanglei Yang
Lifeng Qiao
Zitong Huang
Hongliang Yan
Yunchao Wei
W. Zuo
383
1
0
20 Jun 2024
Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
Zihan Luo
Hong Huang
Yongkang Zhou
Jiping Zhang
Nuo Chen
247
4
0
05 Jun 2024
AI Risk Management Should Incorporate Both Safety and Security
Xiangyu Qi
Yangsibo Huang
Yi Zeng
Edoardo Debenedetti
Jonas Geiping
...
Chaowei Xiao
Yue Liu
Dawn Song
Peter Henderson
Prateek Mittal
AAML
284
21
0
29 May 2024
Safety in Graph Machine Learning: Threats and Safeguards
Song Wang
Yushun Dong
Binchi Zhang
Zihan Chen
Xingbo Fu
Yinhan He
Cong Shen
Chuxu Zhang
Nitesh Chawla
Wenlin Yao
377
11
0
17 May 2024
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models
Anshuman Chhabra
Bo Li
Jian Chen
Prasant Mohapatra
Hongfu Liu
TDI
547
0
0
06 May 2024
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective
Xinjian Luo
Yangfan Jiang
Fei Wei
Yuncheng Wu
Xiaokui Xiao
Beng Chin Ooi
DiffM
386
9
0
28 Feb 2024
The Effect of Data Poisoning on Counterfactual Explanations
André Artelt
Shubham Sharma
Freddy Lecue
Barbara Hammer
487
2
0
13 Feb 2024
TrojFair: Trojan Fairness Attacks
Meng Zheng
Jiaqi Xue
Yi Sheng
Lei Yang
Qian Lou
Lei Jiang
292
4
0
16 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
385
6
0
07 Dec 2023
Survey on AI Ethics: A Socio-technical Perspective
International Conference on Climate Informatics (ICCI), 2023
Dave Mbiazi
Meghana Bhange
Maryam Babaei
Ivaxi Sheth
Patrik Kenfack
Samira Ebrahimi Kahou
428
10
0
28 Nov 2023
Deceptive Fairness Attacks on Graphs via Meta Learning
International Conference on Learning Representations (ICLR), 2023
Jian Kang
Yinglong Xia
Ross Maciejewski
Jiebo Luo
Hanghang Tong
225
9
0
24 Oct 2023
Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang
Yushun Dong
Chen Chen
Yada Zhu
Minnan Luo
Jundong Li
314
7
0
20 Oct 2023
Towards Poisoning Fair Representations
International Conference on Learning Representations (ICLR), 2023
Tianci Liu
Haoyu Wang
Feijie Wu
Hengtong Zhang
Pan Li
Lu Su
Jing Gao
AAML
222
3
0
28 Sep 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey
Information Fusion (Inf. Fusion), 2023
Hubert Baniecki
P. Biecek
AAML
571
129
0
06 Jun 2023
Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures
Computer Vision and Pattern Recognition (CVPR), 2023
Eugenia Iofinova
Alexandra Peste
Dan Alistarh
286
12
0
25 Apr 2023
To be Robust and to be Fair: Aligning Fairness with Robustness
Junyi Chai
Xiaoqian Wang
266
3
0
31 Mar 2023
Improving Fair Training under Correlation Shifts
International Conference on Machine Learning (ICML), 2023
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
234
21
0
05 Feb 2023
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy
Yusuke Kawamoto
Kazumasa Miyake
K. Konishi
Y. Oiwa
266
5
0
18 Jan 2023
A Survey on Preserving Fairness Guarantees in Changing Environments
Ainhize Barrainkua
Paula Gordaliza
Jose A. Lozano
Novi Quadrianto
FaML
418
3
0
14 Nov 2022
Fairness-aware Regression Robust to Adversarial Attacks
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Yulu Jin
Lifeng Lai
FaML
OOD
312
6
0
04 Nov 2022
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework
International Conference on Learning Representations (ICLR), 2022
Anshuman Chhabra
Peizhao Li
P. Mohapatra
Hongfu Liu
OOD
492
28
0
04 Oct 2022
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks
Industrial Conference on Data Mining (IDM), 2022
Hussain Hussain
Meng Cao
Sandipan Sikdar
D. Helic
Elisabeth Lex
M. Strohmaier
Roman Kern
271
19
0
13 Sep 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang
Junyuan Hong
Jiayu Zhou
Zinan Lin
OOD
232
12
0
04 Jul 2022
How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis
Conference on Fairness, Accountability and Transparency (FAccT), 2022
Bishwamittra Ghosh
D. Basu
Kuldeep S. Meel
FaML
269
15
0
01 Jun 2022
Subverting Fair Image Search with Generative Adversarial Perturbations
Conference on Fairness, Accountability and Transparency (FAccT), 2022
A. Ghosh
Matthew Jagielski
Chris L. Wilson
361
8
0
05 May 2022
Robust Conversational Agents against Imperceptible Toxicity Triggers
North American Chapter of the Association for Computational Linguistics (NAACL), 2022
Ninareh Mehrabi
Ahmad Beirami
Fred Morstatter
Aram Galstyan
AAML
282
37
0
05 May 2022
Fairness in Graph Mining: A Survey
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Yushun Dong
Jing Ma
Song Wang
Chen Chen
Jundong Li
FaML
405
163
0
21 Apr 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Machine Intelligence Research (MIR), 2022
Enyan Dai
Tianxiang Zhao
Huaisheng Zhu
Jun Xu
Zhimeng Guo
Hui Liu
Shucheng Zhou
Suhang Wang
367
208
0
18 Apr 2022
Breaking Fair Binary Classification with Optimal Flipping Attacks
International Symposium on Information Theory (ISIT), 2022
Changhun Jo
Jy-yong Sohn
Kangwook Lee
FaML
196
7
0
12 Apr 2022
Towards Multi-Objective Statistically Fair Federated Learning
Ninareh Mehrabi
Cyprien de Lichy
John McKay
C. He
William Campbell
FedML
206
13
0
24 Jan 2022
Interpretable Data-Based Explanations for Fairness Debugging
Romila Pradhan
Jiongli Zhu
Boris Glavic
Babak Salimi
319
67
0
17 Dec 2021
Fairness Degrading Adversarial Attacks Against Clustering Algorithms
Anshuman Chhabra
Adish Singla
P. Mohapatra
276
8
0
22 Oct 2021
Poisoning Attacks on Fair Machine Learning
Minh-Hao Van
Wei Du
Xintao Wu
Aidong Lu
AAML
181
30
0
17 Oct 2021
Machine Learning for Fraud Detection in E-Commerce: A Research Agenda
Niek Tax
Kees Jan de Vries
Mathijs de Jong
Nikoleta Dosoula
Bram van den Akker
Jon Smith
Olivier Thuong
Lucas Bernardi
121
25
0
05 Jul 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data
Eugenia Iofinova
Nikola Konstantinov
Christoph H. Lampert
FaML
397
0
0
22 Jun 2021
Fairness-Aware PAC Learning from Corrupted Data
Journal of machine learning research (JMLR), 2021
Nikola Konstantinov
Christoph H. Lampert
286
22
0
11 Feb 2021
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