@conference {1635074, title = {Private rank aggregation in central and local models.}, booktitle = {In Proceedings of the 2022 AAAI Conference on Artificial Intelligence}, year = {2022}, abstract = {In social choice theory, (Kemeny) rank aggregation is a well-studied problem where the goal is to combine rankings from multiple voters into a single ranking on the same set of items. Since rankings can reveal preferences of voters (which a voter might like to keep private), it is important to aggregate preferences in such a way to preserve privacy. In this work, we present differentially private algorithms for rank aggregation in the pure and approximate settings along with distribution-independent utility upper and lower bounds. In addition to bounds in the central model, we also present utility bounds for the local model of differential privacy.}, url = {https://arxiv.org/pdf/2112.14652.pdf}, author = {Daniel Alabi and Badih Ghazi and Kumar, Ravi and Pasin Manurangsi} }