Talks and Poster Presentations (with Proceedings-Entry):

T. Hamm, M. Lackner, A. Rapberger:
"Computing Kemeny Rankings from d-Euclidean Preferences";
Talk: ADT 2021 - Algorithmic Decision Theory - 7th International Conference, Toulouse, France; 2021-11-03 - 2021-11-05; in: "Algorithmic Decision Theory - 7th International Conference, {ADT} 2021, Toulouse, France, November 3-5, 2021, Proceedings", (2021), 147 - 161.

English abstract:
Kemeny´s voting rule is a well-known and computationally intractable rank aggregation method. In this work, we propose an algorithm that finds an embeddable Kemeny ranking in d-Euclidean elections. This algorithm achieves a polynomial runtime (for a fixed dimension d) and thus demonstrates the algorithmic usefulness of the d-Euclidean restriction. We further investigate how well embeddable Kemeny rankings approximate optimal (unrestricted) Kemeny rankings.

Euclidean preferences Kemeny´s voting rule Rank aggregation algorithms Computational complexity

Created from the Publication Database of the Vienna University of Technology.