We consider the correlation clustering problem which was initially introduced by Bansal, Blum, Chawla et al. Given a complete graph G on n vertices, with weights of +1 or -1 defined on the edges, we want to find a partition which maximizes the sum of the number of edges with positive weights inside the clusters plus the number of edges with negative weights between different clusters. In this thesis we present a deterministic polynomial time approximation scheme for finding such a partition. Our approach is different from the one given by Bansal, Blum, Chawla et al. as it relies on the Szemeredi's Regularity Lemma. We start by introducing the problem, then we introduce the concepts of regularity lemma and give a proof of Szemeredi's Regularity Lemma. Then we present the algorithm and the proof of the correctness of the algorithm.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We consider the correlation clustering problem which was initially introduced by Bansal, Blum, Chawla et al. Given a complete graph G on n vertices, with weights of +1 or -1 defined on the edges, we want to find a partition which maximizes the sum of the number of edges with positive weights inside the clusters plus the number of edges with negative weights between different clusters. In this thesis we present a deterministic polynomial time approximation scheme for finding such a partition. Our approach is different from the one given by Bansal, Blum, Chawla et al. as it relies on the Szemeredi's Regularity Lemma. We start by introducing the problem, then we introduce the concepts of regularity lemma and give a proof of Szemeredi's Regularity Lemma. Then we present the algorithm and the proof of the correctness of the algorithm. 64 pp. Englisch. Bestandsnummer des Verkäufers 9783838313542
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. We consider the correlation clustering problem which was initially introduced by Bansal, Blum, Chawla et al. Given a complete graph G on n vertices, with weights of +1 or -1 defined on the edges, we want to find a partition which maximizes the sum of the nu. Bestandsnummer des Verkäufers 5412048
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We consider the correlation clustering problem which was initially introduced by Bansal, Blum, Chawla et al. Given a complete graph G on n vertices, with weights of +1 or -1 defined on the edges, we want to find a partition which maximizes the sum of the number of edges with positive weights inside the clusters plus the number of edges with negative weights between different clusters. In this thesis we present a deterministic polynomial time approximation scheme for finding such a partition. Our approach is different from the one given by Bansal, Blum, Chawla et al. as it relies on the Szemeredi's Regularity Lemma. We start by introducing the problem, then we introduce the concepts of regularity lemma and give a proof of Szemeredi's Regularity Lemma. Then we present the algorithm and the proof of the correctness of the algorithm.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Bestandsnummer des Verkäufers 9783838313542
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Taschenbuch. Zustand: Neu. On The Correlation Clustering Problem | Algorithm for Correlation Clustering Problem | Sriram Penumatcha | Taschenbuch | 64 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838313542 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 101381972
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