Deterministic pivoting algorithms for constrained ranking and clustering problems1
نویسندگان
چکیده
We consider ranking and clustering problems related to the aggregation of inconsistent information, in particular, rank aggregation, (weighted) feedback arc set in tournaments, consensus and correlation clustering, and hierarchical clustering. Ailon, Charikar, and Newman [4], Ailon and Charikar [3], and Ailon [2] proposed randomized constant factor approximation algorithms for these problems, which recursively generate a solution by choosing a random vertex as “pivot” and dividing the remaining vertices into two groups based on the pivot vertex.
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Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems
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