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The authors introduce, model and solve private non-transitive preference-based stable matching using a new optimization framework that models privacy-loss as utility loss. Classic stable matching problems are a well known tractable application with many uses. However, some versions of stable matching problems are not tractable. One such version that they identified earlier is the stable matching with privacy of preferences. Privacy of preferences requirements precludes centralization of the data for running efficient algorithms. Distributed solving has to minimize privacy loss.
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