SpatialFlip: A Postprocessing Method to Improve Spatial Fairness

Author:

Arroyo Victor1ORCID,Sacharidis Dimitris2ORCID

Affiliation:

1. Université Libre de Bruxelles, Jette, Brussels, Belgium

2. Université Libre de Bruxelles, Brussels, Belgium

Publisher

ACM

Reference5 articles.

1. Realizing Racial and Ethnic Neighborhood Preferences? Exploring the Mismatches Between What People Want, Where They Search, and Where They Live

2. Evaggelia Pitoura , Kostas Stefanidis , and Georgia Koutrika . 2021. Fairness in Rankings and Recommendations: An Overview. CoRR abs/2104.05994 ( 2021 ). arXiv:2104.05994 https://arxiv.org/abs/2104.05994 Evaggelia Pitoura, Kostas Stefanidis, and Georgia Koutrika. 2021. Fairness in Rankings and Recommendations: An Overview. CoRR abs/2104.05994 (2021). arXiv:2104.05994 https://arxiv.org/abs/2104.05994

3. Models and mechanisms for spatial data fairness

4. Yiqun Xie , Erhu He , Xiaowei Jia , Weiye Chen , Sergii Skakun , Han Bao , Zhe Jiang , Rahul Ghosh , and Praveen Ravirathinam . 2022. Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework . In AAAI. AAAI Press , 12208--12216. Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, and Praveen Ravirathinam. 2022. Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework. In AAAI. AAAI Press, 12208--12216.

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