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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]