Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence 2021
DOI: 10.24963/ijcai.2021/2
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Diversity in Kemeny Rank Aggregation: A Parameterized Approach

Abstract: In its most traditional setting, the main concern of optimization theory is the search for optimal solutions for instances of a given computational problem. A recent trend of research in artificial intelligence, called solution diversity, has focused on the development of notions of optimality that may be more appropriate in settings where subjectivity is essential. The idea is that instead of aiming at the development of algorithms that output a single optimal solution, the goal is to investigate algorithms t… Show more

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Cited by 5 publications
(3 citation statements)
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“…Furthermore, in machine learning efforts to bridge the gap between fairness and explainability were made (Zhao, Wang, and Derr 2023). There's also a trend on discovering diverse solutions (Arrighi et al 2023), which offers different choices at various stages, which can be used to uphold fairness. Exploring fairness issues using the explainable framework presented here will be explored in future research and can be addressed by appropriately adapting parameters λ i in model (Exp) such that similarities in unpopular or recent situations is avoided.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, in machine learning efforts to bridge the gap between fairness and explainability were made (Zhao, Wang, and Derr 2023). There's also a trend on discovering diverse solutions (Arrighi et al 2023), which offers different choices at various stages, which can be used to uphold fairness. Exploring fairness issues using the explainable framework presented here will be explored in future research and can be addressed by appropriately adapting parameters λ i in model (Exp) such that similarities in unpopular or recent situations is avoided.…”
Section: Discussionmentioning
confidence: 99%
“…Alternatively, we could restrict ourselves to only computing multiple solutions on the sub-instances and use classical post processing in order to compute all topological orderings of the strict majority graph and concatenate the solutions of the sub-instances accordingly. It is not hard to see that once we have the strongly connected components, computing a diverse set of topological orderings can be done by seeing the problem as an instance of the Completion of an Ordering problem with all costs set to 1 and using the parameterized algorithm for the diverse version proposed in [Arrighi et al, 2021].…”
Section: Extended Condorcet Rulementioning
confidence: 99%
“…The practical relevance in the field of artificial intelligence is also highlighted by a series of experimental studies of heuristics and approximations of the KRA problem [Ali and Meila, 2012, Davenport andKalagnanam, 2004] as well as experimental studies of lower bounds for exact solutions of KRA [Conitzer et al, 2006, Schalekamp and. A parameterized algorithm for a diverse version of Kemeny Rank Aggregation recently appeared at IJCAI [Arrighi et al, 2021].…”
Section: Introductionmentioning
confidence: 99%