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A Survey on Fairness for Machine Learning on Graphs
[article]
2024
arXiv
pre-print
Nowadays, the analysis of complex phenomena modeled by graphs plays a crucial role in many real-world application domains where decisions can have a strong societal impact. However, numerous studies and papers have recently revealed that machine learning models could lead to potential disparate treatment between individuals and unfair outcomes. In that context, algorithmic contributions for graph mining are not spared by the problem of fairness and present some specific challenges related to
arXiv:2205.05396v2
fatcat:cf4rbo36bvfypigdqcsfq3lfma