Compositional Fairness Constraints for Graph Embeddings

25 May 2019

Papers citing "Compositional Fairness Constraints for Graph Embeddings"

50 / 56 papers shown

Title
Social Biases in Knowledge Representations of Wikidata separates Global North from Global South Paramita Das Sai Keerthana Karnam Aditya Soni Animesh Mukherjee 177 0 0 05 May 2025
Causally Fair Node Classification on Non-IID Graph Data Yucong Dai Lu Zhang Yaowei Hu Susan Gauch Yongkai Wu FaML 55 0 0 03 May 2025
Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization Hongxu Wang Zhu Sun Yingpeng Du Lu Zhang Tiantian He Yew-Soon Ong 61 0 0 18 Feb 2025
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Ruizhan Xue Huimin Deng Fang He Maojun Wang Zeyu Zhang 75 1 0 12 Feb 2025
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage Ying Song Balaji Palanisamy 87 0 0 28 Jan 2025
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion Abdullah Alchihabi Yuhong Guo DiffM 30 0 0 03 Jan 2025
Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis Dacao Zhang Kun Zhang Le Wu Mi Tian Richang Hong Ming Wang 43 5 0 05 Jun 2024
FairSTG: Countering performance heterogeneity via collaborative sample-level optimization Gengyu Lin Zhen-Qiang Zhou Qihe Huang Kuo Yang Shifen Cheng Yang Wang AI4TS 32 1 0 19 Mar 2024
Graph Fairness Learning under Distribution Shifts Yibo Li Xiao Wang Yujie Xing Shaohua Fan Ruijia Wang Yaoqi Liu Chuan Shi OOD 43 7 0 30 Jan 2024
Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models Jorge Paz-Ruza Amparo Alonso-Betanzos B. Guijarro-Berdiñas Brais Cancela Carlos Eiras-Franco 58 2 0 19 Jan 2024
Compositional Fusion of Signals in Data Embedding Zhijin Guo Zhaozhen Xu Martha Lewis N. Cristianini 24 0 0 18 Nov 2023
Better Fair than Sorry: Adversarial Missing Data Imputation for Fair GNNs Debolina Halder Lina Arlei Silva 33 0 0 02 Nov 2023
Deceptive Fairness Attacks on Graphs via Meta Learning Jian Kang Yinglong Xia Ross Maciejewski Jiebo Luo Hanghang Tong 44 4 0 24 Oct 2023
Marginal Nodes Matter: Towards Structure Fairness in Graphs Xiaotian Han Kaixiong Zhou Ting-Hsiang Wang Jundong Li Fei Wang Na Zou 36 0 0 23 Oct 2023
Adversarial Attacks on Fairness of Graph Neural Networks Binchi Zhang Yushun Dong Chen Chen Yada Zhu Minnan Luo Jundong Li 55 3 0 20 Oct 2023
A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions Zemin Liu Yuan N. Li Nan-Fang Chen Qian Wang Bryan Hooi Bin He FaML 21 13 0 26 Aug 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu Yuhang Zhou Bang An Wei Ai Furong Huang 37 6 0 25 May 2023
Graph Neural Network Surrogates of Fair Graph Filtering Emmanouil Krasanakis Symeon Papadopoulos 35 1 0 14 Mar 2023
Travel Demand Forecasting: A Fair AI Approach Xiaojian Zhang Qian Ke Xilei Zhao AI4TS 35 3 0 03 Mar 2023
Fair Attribute Completion on Graph with Missing Attributes Dongliang Guo Zhixuan Chu Sheng Li FaML 38 18 0 25 Feb 2023
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks Indro Spinelli Riccardo Bianchini Simone Scardapane 33 1 0 22 Feb 2023
Biases in Scholarly Recommender Systems: Impact, Prevalence, and Mitigation Michael Färber Melissa Coutinho Shuzhou Yuan 34 7 0 18 Jan 2023
Mitigating Relational Bias on Knowledge Graphs Yu-Neng Chuang Kwei-Herng Lai Ruixiang Tang Mengnan Du Chia-Yuan Chang Na Zou Xia Hu FaML 29 5 0 26 Nov 2022
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation Nan Wang Qifan Wang Yi-Chia Wang Maziar Sanjabi Jingzhou Liu Hamed Firooz Hongning Wang Shaoliang Nie 33 6 0 14 Oct 2022
BiaScope: Visual Unfairness Diagnosis for Graph Embeddings Agapi Rissaki Bruno Scarone David Liu Aditeya Pandey Brennan Klein Tina Eliassi-Rad M. Borkin FaML 21 6 0 12 Oct 2022
Detecting Political Biases of Named Entities and Hashtags on Twitter Zhiping Xiao Jeffrey Zhu Yining Wang Pei Zhou Wen Hong Lam M. A. Porter Yizhou Sun 41 18 0 16 Sep 2022
Analyzing the Effect of Sampling in GNNs on Individual Fairness Rebecca Salganik Fernando Diaz G. Farnadi 26 1 0 08 Sep 2022
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage Yu-Chiang Frank Wang Yuying Zhao Yushun Dong Huiyuan Chen Jundong Li Tyler Derr 32 81 0 07 Jun 2022
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning Tao Qi Fangzhao Wu Chuhan Wu Lingjuan Lyu Tongye Xu Zhongliang Yang Yongfeng Huang Xing Xie FedML 49 36 0 07 Jun 2022
FairNorm: Fair and Fast Graph Neural Network Training Öykü Deniz Köse Yanning Shen AI4CE 23 4 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 47 104 0 16 May 2022
A Survey on Fairness for Machine Learning on Graphs Charlotte Laclau C. Largeron Manvi Choudhary FaML 17 23 0 11 May 2022
FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings Cheng-Te Li Cheng-Mao Hsu Yang Zhang FaML 27 35 0 30 Apr 2022
Joint Multisided Exposure Fairness for Recommendation Haolun Wu Bhaskar Mitra Chen Ma Fernando Diaz Xue Liu FaML 24 64 0 29 Apr 2022
Fairness in Graph Mining: A Survey Yushun Dong Jing Ma Song Wang Chen Chen Jundong Li FaML 34 114 0 21 Apr 2022
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification Sean Current Yuntian He Saket Gurukar Srinivas Parthasarathy 33 13 0 27 Jan 2022
Learning Fair Node Representations with Graph Counterfactual Fairness Jing Ma Ruocheng Guo Mengting Wan Longqi Yang Aidong Zhang Jundong Li FaML 20 79 0 10 Jan 2022
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 37 36 0 04 Nov 2021
Residual2Vec: Debiasing graph embedding with random graphs Sadamori Kojaku Jisung Yoon I. Constantino Yong-Yeol Ahn CML 45 23 0 14 Oct 2021
Efficient Algorithms For Fair Clustering with a New Fairness Notion Shivam Gupta Ganesh Ghalme N. C. Krishnan Shweta Jain FaML 73 8 0 02 Sep 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 36 118 0 11 Aug 2021
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 104 197 0 12 Jul 2021
Subgroup Generalization and Fairness of Graph Neural Networks Jiaqi Ma Junwei Deng Qiaozhu Mei 26 80 0 29 Jun 2021
Personalized Counterfactual Fairness in Recommendation Yunqi Li Hanxiong Chen Shuyuan Xu Yingqiang Ge Yongfeng Zhang FaML OffRL 29 142 0 20 May 2021
TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers Yao Wu Jian Cao Guandong Xu Yudong Tan FaML 27 84 0 19 Apr 2021
Towards a Unified Framework for Fair and Stable Graph Representation Learning Chirag Agarwal Himabindu Lakkaraju Marinka Zitnik 27 157 0 25 Feb 2021
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources Xiao Wang Deyu Bo C. Shi Shaohua Fan Yanfang Ye Philip S. Yu AI4TS 38 295 0 30 Nov 2020
Information Obfuscation of Graph Neural Networks Peiyuan Liao Han Zhao Keyulu Xu Tommi Jaakkola Geoffrey J. Gordon Stefanie Jegelka Ruslan Salakhutdinov AAML 23 34 0 28 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 16 241 0 03 Sep 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 24 287 0 07 May 2020