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UID:845@lincs.fr
DTSTART;TZID=Europe/Paris:20241106T140000
DTEND;TZID=Europe/Paris:20241106T150000
DTSTAMP:20241113T153948Z
URL:https://www.lincs.fr/events/the-squared-kemeny-rule-for-averaging-rank
 ings/
SUMMARY:The Squared Kemeny Rule for Averaging Rankings
DESCRIPTION:\n\nFor the problem of aggregating several rankings into one
 ranking\, Kemeny (1959) proposed two methods: the median rule which selects
 the ranking with the smallest total swap distance to the input rankings\,
 and the mean rule which minimizes the squared swap distances to the input
 rankings. The median rule has been extensively studied since and is now
 known simply as Kemeny's rule. It exhibits majoritarian properties\, so for
 example if more than half of the input rankings are the same\, then the
 output of the rule is the same ranking.\n\nWe observe that this behavior is
 undesirable in many rank aggregation settings. For example\, when we rank
 objects by different criteria (quality\, price\, etc.) and want to
 aggregate them with specified weights for the criteria\, then a criterion
 with weight 51% should have 51% influence on the output instead of 100%. We
 show that the Squared Kemeny rule (i.e.\, the mean rule) behaves this way\,
 by establishing a bound on the distance of the output ranking to any input
 rankings\, as a function of their weights. Furthermore\, we give an
 axiomatic characterization of the Squared Kemeny rule\, which mirrors the
 existing characterization of the Kemeny rule but replaces the majoritarian
 Condorcet axiom by a proportionality axiom. Finally\, we discuss the
 computation of the rule and show its behavior in a simulation
 study.\n\n\nJoint work with Patrick Lederer and Tomasz W?s.
CATEGORIES:Seminars,Youtube
LOCATION:Amphi 6\, 19 Place Marguerite Perey\, Palaiseau\, France
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 Palaiseau\, France;X-APPLE-RADIUS=100;X-TITLE=Amphi 6:geo:0,0
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
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DTSTART:20241027T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
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