Fair-SMW uses SMW identity and alternative Laplacians to produce group-fair spectral clustering that is twice as fast and twice as balanced as prior methods on SBM and real network data.
Narayanan, Tutorial: 21 fairness definitions and their implications , Tutorial at the 2020 Conference on Fairness, Accountability, and Transparency (FAT* ’20), (2020)
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Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints
Fair-SMW uses SMW identity and alternative Laplacians to produce group-fair spectral clustering that is twice as fast and twice as balanced as prior methods on SBM and real network data.