Private Rank Aggregation in Central and Local Models

In social choice theory, (Kemeny) rank aggregation is a well-studied problem where the goal to combine rankings from multiple voters into single ranking on same set of items. Since can reveal preferences (which voter might like keep private), it important aggregate in such way preserve privacy. this work, we present differentially private algorithms for pure and approximate settings along with distribution-independent utility upper lower bounds. addition bounds central model, also local model differential