MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training
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MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit

25 September 2019

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Papers citing "MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit"

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Title
Fairness and/or Privacy on Social Graphs Bartlomiej Surma Michael Backes Yang Zhang 277 0 0 03 Mar 2025
Fair Graph Machine Learning under Adversarial Missingness Processes Debolina Halder Lina Arlei Silva 416 0 0 02 Nov 2023
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 145 7 0 22 Dec 2022
A Survey on Fairness for Machine Learning on Graphs Charlotte Laclau C. Largeron Manvi Choudhary FaML 272 32 0 11 May 2022
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 340 152 0 21 Apr 2022
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 342 188 0 18 Apr 2022
Unbiased Graph Embedding with Biased Graph Observations Nan Wang Lu Lin Jundong Li Hongning Wang CML 266 46 0 26 Oct 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural NetworksThe Web Conference (WWW), 2021 Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 282 158 0 11 Aug 2021
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 317 323 0 07 May 2020
DeBayes: a Bayesian Method for Debiasing Network EmbeddingsInternational Conference on Machine Learning (ICML), 2020 Maarten Buyl T. D. Bie FaML CML 317 85 0 26 Feb 2020