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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2012.226
|2 doi
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|a eng
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|a Rota Bulò, Samuel
|e verfasserin
|4 aut
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|a A game-theoretic approach to hypergraph clustering
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|c 2013
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|a Text
|b txt
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 15.11.2013
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|a Date Revised 19.04.2013
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|a published: Print
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|a Citation Status MEDLINE
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|a Hypergraph clustering refers to the process of extracting maximally coherent groups from a set of objects using high-order (rather than pairwise) similarities. Traditional approaches to this problem are based on the idea of partitioning the input data into a predetermined number of classes, thereby obtaining the clusters as a by-product of the partitioning process. In this paper, we offer a radically different view of the problem. In contrast to the classical approach, we attempt to provide a meaningful formalization of the very notion of a cluster and we show that game theory offers an attractive and unexplored perspective that serves our purpose well. To this end, we formulate the hypergraph clustering problem in terms of a noncooperative multiplayer "clustering game," and show that a natural notion of a cluster turns out to be equivalent to a classical (evolutionary) game-theoretic equilibrium concept. We prove that the problem of finding the equilibria of our clustering game is equivalent to locally optimizing a polynomial function over the standard simplex, and we provide a discrete-time high-order replicator dynamics to perform this optimization, based on the Baum-Eagon inequality. Experiments over synthetic as well as real-world data are presented which show the superiority of our approach over the state of the art
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Pelillo, Marcello
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 35(2013), 6 vom: 15. Juni, Seite 1312-27
|w (DE-627)NLM098212257
|x 1939-3539
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|g year:2013
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|g day:15
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|g pages:1312-27
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|u http://dx.doi.org/10.1109/TPAMI.2012.226
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