Journal ArticleDOI
A randomized approximation algorithm for computing bucket orders
TLDR
It is shown that a simple randomized algorithm has an expected constant factor approximation guarantee for fitting bucket orders to a set of pairwise preferences.About:
This article is published in Information Processing Letters.The article was published on 2009-03-01. It has received 28 citations till now. The article focuses on the topics: Approximation algorithm & Randomized algorithm.read more
Citations
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Book ChapterDOI
Preference Learning: An Introduction
TL;DR: This introduction gives a brief overview of the field of preference learning and tries to establish a unified terminology, proposing a categorization of ranking problems into object ranking, instance ranking, and label ranking.
Proceedings Article
Crowdsourced Nonparametric Density Estimation Using Relative Distances
TL;DR: This work provides two novel methods for density estimation that only use relative expressions of similarity, and gives both theoretical justifications, as well as empirical evidence that the proposed methods produce good estimates.
Journal ArticleDOI
A differential evolution algorithm for finding the median ranking under the Kemeny axiomatic approach
TL;DR: An accurate (meta)heuristic solution to the rank aggregation problem is proposed and is particularly feasible when working with a very large number of objects to be ranked, because it is accurate and also faster than other proposals.
Journal ArticleDOI
Approaching rank aggregation problems by using evolution strategies: The case of the optimal bucket order problem
TL;DR: The study shows that the best evolution strategy improves upon the accuracy obtained by the standard greedy method (BPA) by 35%, and that of LIA G M P 2 by 12.5%.
Journal ArticleDOI
Utopia in the solution of the Bucket Order Problem
TL;DR: This paper deals with group decision making and, in particular, with rank aggregation, which is the problem of aggregating individual preferences (rankings) in order to obtain a consensus ranking, and proposes two improvements to the standard greedy algorithm usually considered to approach the bucket order problem: the Bucket Pivot Algorithm (BPA).
References
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Book
Computers and Intractability: A Guide to the Theory of NP-Completeness
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI
Aggregating inconsistent information: Ranking and clustering
TL;DR: This work almost settles a long-standing conjecture of Bang-Jensen and Thomassen and shows that unless NP⊆BPP, there is no polynomial time algorithm for the problem of minimum feedback arc set in tournaments.
Proceedings ArticleDOI
How to rank with few errors
TL;DR: A polynomial time approximation scheme (PTAS) for the minimum feedback arc set problem on tournaments and a simple weighted generalization gives a PTAS for Kemeny-Young rank aggregation.