Parameterizing above guaranteed values: MaxSat and MaxCut
Journal of Algorithms
A general method to speed up fixed-parameter-tractable algorithms
Information Processing Letters
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Algorithm Design
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
The complexity of Kemeny elections
Theoretical Computer Science
Invitation to data reduction and problem kernelization
ACM SIGACT News
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Improved fixed parameter tractable algorithms for two “edge” problems: MAXCUT and MAXDAG
Information Processing Letters
A fixed-parameter algorithm for the directed feedback vertex set problem
Journal of the ACM (JACM)
Aggregating inconsistent information: Ranking and clustering
Journal of the ACM (JACM)
A computational study of the Kemeny rule for preference aggregation
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Computing slater rankings using similarities among candidates
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Improved bounds for computing Kemeny rankings
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Llull and copeland voting broadly resist bribery and control
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Parameterized complexity of candidate control in elections and related digraph problems
Theoretical Computer Science
Preference functions that score rankings and maximum likelihood estimation
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Deterministic algorithms for rank aggregation and other ranking and clustering problems
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
Towards a dichotomy for the Possible Winner problem in elections based on scoring rules
Journal of Computer and System Sciences
Average parameterization and partial kernelization for computing medians
Journal of Computer and System Sciences
Average parameterization and partial kernelization for computing medians
LATIN'10 Proceedings of the 9th Latin American conference on Theoretical Informatics
Comparing and aggregating partial orders with kendall tau distances
WALCOM'12 Proceedings of the 6th international conference on Algorithms and computation
Cloning in elections: finding the possible winners
Journal of Artificial Intelligence Research
Studies in computational aspects of voting: open problems of downey and fellows
The Multivariate Algorithmic Revolution and Beyond
Designing social choice mechanisms using machine learning
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Parameterized enumeration of (locally-) optimal aggregations
WADS'13 Proceedings of the 13th international conference on Algorithms and Data Structures
Kemeny elections with bounded single-peaked or single-crossing width
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Fully proportional representation as resource allocation: approximability results
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Hi-index | 5.23 |
The computation of Kemeny rankings is central to many applications in the context of rank aggregation. Given a set of permutations (votes) over a set of candidates, one searches for a ''consensus permutation'' that is ''closest'' to the given set of permutations. Unfortunately, the problem is NP-hard. We provide a broad study of the parameterized complexity for computing optimal Kemeny rankings. Besides the three obvious parameters ''number of votes'', ''number of candidates'', and solution size (called Kemeny score), we consider further structural parameterizations. More specifically, we show that the Kemeny score (and a corresponding Kemeny ranking) of an election can be computed efficiently whenever the average pairwise distance between two input votes is not too large. In other words, Kemeny Score is fixed-parameter tractable with respect to the parameter ''average pairwise Kendall-Tau distance d"a''. We describe a fixed-parameter algorithm with running time 16^@?^d^"^a^@?@?poly. Moreover, we extend our studies to the parameters ''maximum range'' and ''average range'' of positions a candidate takes in the input votes. Whereas Kemeny Score remains fixed-parameter tractable with respect to the parameter ''maximum range'', it becomes NP-complete in the case of an average range of two. This excludes fixed-parameter tractability with respect to the parameter ''average range'' unless P=NP. Finally, we extend some of our results to votes with ties and incomplete votes, where in both cases one no longer has permutations as input.