Fairness-in-NRL

• Fair Representation Learning for Heterogeneous Information Networks. AAAI, 2021, pdf
• List-wise Fairness Criterion for Point Processes, KDD, 2020, pdf
• Du, Xin, et al. "Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data." AAAI. 2020. pdf
• Buyl, Maarten, and Tijl De Bie. "DeBayes: a Bayesian method for debiasing network embeddings." arXiv preprint arXiv:2002.11442 (2020). pdf
• Creager, E., Madras, D., Jacobsen, J., Weis, M., Swersky, K., Pitassi, T. & Zemel, R.. (2019). Flexibly Fair Representation Learning by Disentanglement. Proceedings of the 36th International Conference on Machine Learning, in PMLR 97:1436-1445 pdf
• Rahman, Tahleen A., et al. "Fairwalk: Towards Fair Graph Embedding." IJCAI. 2019.pdf
• Bose, Avishek, and William Hamilton. "Compositional fairness constraints for graph embeddings." International Conference on Machine Learning. PMLR, 2019. pdf [Code]