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Say No to the Discrimination: Learning Fair Graph Neural Networks with
  Limited Sensitive Attribute Information
v1v2v3v4v5 (latest)

Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

Web Search and Data Mining (WSDM), 2020
3 September 2020
Enyan Dai
Suhang Wang
    FaML
ArXiv (abs)PDFHTMLHuggingFace (1 upvotes)

Papers citing "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information"

43 / 93 papers shown
Unnoticeable Backdoor Attacks on Graph Neural Networks
Unnoticeable Backdoor Attacks on Graph Neural NetworksThe Web Conference (WWW), 2023
Enyan Dai
Minhua Lin
Xiang Zhang
Suhang Wang
AAML
274
72
0
11 Feb 2023
On Generalized Degree Fairness in Graph Neural Networks
On Generalized Degree Fairness in Graph Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2023
Zemin Liu
Trung-Kien Nguyen
Yuan Fang
183
38
0
08 Feb 2023
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic
  Parity
Retiring ΔΔΔDP: New Distribution-Level Metrics for Demographic Parity
Xiaotian Han
Zhimeng Jiang
Hongye Jin
Zirui Liu
Na Zou
Qifan Wang
Helen Zhou
373
4
0
31 Jan 2023
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
Unraveling Privacy Risks of Individual Fairness in Graph Neural NetworksIEEE International Conference on Data Engineering (ICDE), 2023
He Zhang
Lizhen Qu
Shirui Pan
257
19
0
30 Jan 2023
A Comparative Analysis of Bias Amplification in Graph Neural Network
  Approaches for Recommender Systems
A Comparative Analysis of Bias Amplification in Graph Neural Network Approaches for Recommender Systems
Nikzad Chizari
Niloufar Shoeibi
María N. Moreno-García
155
17
0
18 Jan 2023
RELIANT: Fair Knowledge Distillation for Graph Neural Networks
RELIANT: Fair Knowledge Distillation for Graph Neural NetworksSDM (SDM), 2023
Yushun Dong
Binchi Zhang
Yiling Yuan
Na Zou
Qi Wang
Jundong Li
370
15
0
03 Jan 2023
Graph Learning with Localized Neighborhood Fairness
Graph Learning with Localized Neighborhood Fairness
April Chen
Ryan Rossi
Nedim Lipka
Jane Hoffswell
G. Chan
Shunan Guo
Eunyee Koh
Sungchul Kim
Nesreen K. Ahmed
FaML
158
7
0
22 Dec 2022
Mitigating Relational Bias on Knowledge Graphs
Mitigating Relational Bias on Knowledge GraphsACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Yu-Neng Chuang
Kwei-Herng Lai
Ruixiang Tang
Mengnan Du
Chia-Yuan Chang
Na Zou
Helen Zhou
FaML
225
5
0
26 Nov 2022
Interpreting Unfairness in Graph Neural Networks via Training Node
  Attribution
Interpreting Unfairness in Graph Neural Networks via Training Node AttributionAAAI Conference on Artificial Intelligence (AAAI), 2022
Yushun Dong
Song Wang
Jing Ma
Ninghao Liu
Jundong Li
204
29
0
25 Nov 2022
FairMILE: Towards an Efficient Framework for Fair Graph Representation
  Learning
FairMILE: Towards an Efficient Framework for Fair Graph Representation LearningConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022
Yuntian He
Saket Gurukar
Srinivas Parthasarathy
FaML
464
7
0
17 Nov 2022
Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph
  Node Classifiers
Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers
Haris Mansoor
Sarwan Ali
Shafiq Alam
Muhammad Asad Khan
U. Hassan
Imdadullah Khan
FaML
166
5
0
01 Nov 2022
Efficient first-order predictor-corrector multiple objective
  optimization for fair misinformation detection
Efficient first-order predictor-corrector multiple objective optimization for fair misinformation detection
Eric Enouen
Katja Mathesius
Sean Wang
Arielle K. Carr
Sihong Xie
97
2
0
15 Sep 2022
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph
  Neural Networks
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural NetworksIndustrial Conference on Data Mining (IDM), 2022
Hussain Hussain
Meng Cao
Sandipan Sikdar
D. Helic
Elisabeth Lex
M. Strohmaier
Roman Kern
239
18
0
13 Sep 2022
On Graph Neural Network Fairness in the Presence of Heterophilous
  Neighborhoods
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods
Donald Loveland
Jiong Zhu
Mark Heimann
Benjamin Fish
Michael T. Schaub
Danai Koutra
214
6
0
10 Jul 2022
Source Localization of Graph Diffusion via Variational Autoencoders for
  Graph Inverse Problems
Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse ProblemsKnowledge Discovery and Data Mining (KDD), 2022
Chen Ling
Junji Jiang
Junxiang Wang
Bo Pan
DiffM
201
59
0
24 Jun 2022
On Structural Explanation of Bias in Graph Neural Networks
On Structural Explanation of Bias in Graph Neural NetworksKnowledge Discovery and Data Mining (KDD), 2022
Yushun Dong
Song Wang
Yu Wang
Hanyu Wang
Jundong Li
176
34
0
24 Jun 2022
Improving Fairness in Graph Neural Networks via Mitigating Sensitive
  Attribute Leakage
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute LeakageKnowledge Discovery and Data Mining (KDD), 2022
Yu Wang
Yuying Zhao
Yushun Dong
Huiyuan Chen
Jundong Li
Hanyu Wang
333
110
0
07 Jun 2022
FairNorm: Fair and Fast Graph Neural Network Training
FairNorm: Fair and Fast Graph Neural Network Training
Öykü Deniz Köse
Yanning Shen
AI4CE
144
5
0
20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and TrendsProceedings of the IEEE (Proc. IEEE), 2022
He Zhang
Bang Wu
Lizhen Qu
Shirui Pan
Hanghang Tong
Jian Pei
373
150
0
16 May 2022
A Survey on Fairness for Machine Learning on Graphs
A Survey on Fairness for Machine Learning on Graphs
Charlotte Laclau
C. Largeron
Manvi Choudhary
FaML
278
33
0
11 May 2022
Fairness in Graph Mining: A Survey
Fairness in Graph Mining: A SurveyIEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Yushun Dong
Jing Ma
Song Wang
Chen Chen
Jundong Li
FaML
378
153
0
21 Apr 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy,
  Robustness, Fairness, and Explainability
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and ExplainabilityMachine Intelligence Research (MIR), 2022
Enyan Dai
Tianxiang Zhao
Huaisheng Zhu
Jun Xu
Zhimeng Guo
Hui Liu
Shucheng Zhou
Suhang Wang
360
193
0
18 Apr 2022
Distraction is All You Need for Fairness
Distraction is All You Need for Fairness
Mehdi Yazdani-Jahromi
Amirarsalan Rajabi
Ali Khodabandeh Yalabadi
Aida Tayebi
O. Garibay
331
4
0
15 Mar 2022
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional
  Network
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional NetworkThe Web Conference (WWW), 2022
Jian Kang
Yangchun Zhu
Yinglong Xia
Jiebo Luo
Hanghang Tong
FaML
170
52
0
28 Feb 2022
Obtaining Dyadic Fairness by Optimal Transport
Obtaining Dyadic Fairness by Optimal Transport
Moyi Yang
Junjie Sheng
Xiangfeng Wang
Wenyan Liu
Bo Jin
Jun Wang
H. Zha
230
7
0
09 Feb 2022
FMP: Toward Fair Graph Message Passing against Topology Bias
FMP: Toward Fair Graph Message Passing against Topology Bias
Zhimeng Jiang
Xiaotian Han
Chao Fan
Zirui Liu
Na Zou
Ali Mostafavi
Helen Zhou
147
50
0
08 Feb 2022
Fair Node Representation Learning via Adaptive Data Augmentation
Fair Node Representation Learning via Adaptive Data Augmentation
Öykü Deniz Köse
Yanning Shen
108
38
0
21 Jan 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy
  Graph Editing
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
Donald Loveland
Jiayi Pan
A. Bhathena
Yiyang Lu
156
22
0
10 Jan 2022
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse LabelsWeb Search and Data Mining (WSDM), 2022
Enyan Dai
Wei Jin
Hui Liu
Suhang Wang
NoLa
268
116
0
01 Jan 2022
Unbiased Graph Embedding with Biased Graph Observations
Unbiased Graph Embedding with Biased Graph Observations
Nan Wang
Lu Lin
Jundong Li
Hongning Wang
CML
291
46
0
26 Oct 2021
Label-Wise Graph Convolutional Network for Heterophilic Graphs
Label-Wise Graph Convolutional Network for Heterophilic Graphs
Enyan Dai
Shijie Zhou
Zhimeng Guo
Suhang Wang
270
22
0
15 Oct 2021
Towards Self-Explainable Graph Neural Network
Towards Self-Explainable Graph Neural NetworkInternational Conference on Information and Knowledge Management (CIKM), 2021
Enyan Dai
Suhang Wang
270
101
0
26 Aug 2021
EqGNN: Equalized Node Opportunity in Graphs
EqGNN: Equalized Node Opportunity in Graphs
Uriel Singer
Kira Radinsky
139
8
0
19 Aug 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks
EDITS: Modeling and Mitigating Data Bias for Graph Neural NetworksThe Web Conference (WWW), 2021
Yushun Dong
Ninghao Liu
B. Jalaeian
Jundong Li
315
159
0
11 Aug 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
Shucheng Zhou
FaML
405
258
0
12 Jul 2021
Subgroup Generalization and Fairness of Graph Neural Networks
Subgroup Generalization and Fairness of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2021
Jiaqi Ma
Junwei Deng
Qiaozhu Mei
247
91
0
29 Jun 2021
Is Homophily a Necessity for Graph Neural Networks?
Is Homophily a Necessity for Graph Neural Networks?International Conference on Learning Representations (ICLR), 2021
Yao Ma
Xiaorui Liu
Neil Shah
Shucheng Zhou
296
275
0
11 Jun 2021
Automated Self-Supervised Learning for Graphs
Automated Self-Supervised Learning for GraphsInternational Conference on Learning Representations (ICLR), 2021
Wei Jin
Xiaorui Liu
Xiangyu Zhao
Yao Ma
Neil Shah
Shucheng Zhou
SSL
336
88
0
10 Jun 2021
Fairness-Aware Node Representation Learning
Fairness-Aware Node Representation Learning
Öykü Deniz Köse
Yanning Shen
143
22
0
09 Jun 2021
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely
  and Noisily Labeled Graphs
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled GraphsKnowledge Discovery and Data Mining (KDD), 2021
Enyan Dai
Charu C. Aggarwal
Suhang Wang
NoLa
187
141
0
08 Jun 2021
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases
  in Related Features
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related FeaturesWeb Search and Data Mining (WSDM), 2021
Tianxiang Zhao
Enyan Dai
Kai Shu
Suhang Wang
FaML
284
70
0
29 Apr 2021
Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation
Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation
Yi Sun
Abel N. Valente
Sijia Liu
Dakuo Wang
AAML
173
7
0
25 Mar 2021
Graph Neural Networks in Recommender Systems: A Survey
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu
Fei Sun
Wentao Zhang
Xu Xie
Tengjiao Wang
GNN
838
1,564
0
04 Nov 2020
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