Dense graph

Results: 61



#Item
1Graph Algorithms Representations of graph G with vertices V and edges E ● V x V adjacency-matrix A: Au, v = 1  (u, v) ∈ E Size: |V|2 Better for dense graphs, i.e., |E| = Ω(|V|2)

Graph Algorithms Representations of graph G with vertices V and edges E ● V x V adjacency-matrix A: Au, v = 1  (u, v) ∈ E Size: |V|2 Better for dense graphs, i.e., |E| = Ω(|V|2)

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Source URL: www.ccs.neu.edu

Language: English - Date: 2013-11-01 09:55:34
    2Noname manuscript No. (will be inserted by the editor) Subjective interestingness of subgraph patterns Matthijs van Leeuwen · Tijl De Bie · Eirini Spyropoulou · C´

    Noname manuscript No. (will be inserted by the editor) Subjective interestingness of subgraph patterns Matthijs van Leeuwen · Tijl De Bie · Eirini Spyropoulou · C´

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    Source URL: www.patternsthatmatter.org

    Language: English - Date: 2016-01-15 06:48:18
    3Discovering dense subgraphs and understanding their relations is important. Peeling algorithms (k-core, k-truss, and nucleus decomposition) have been shown to be effective to locate many dense subgraphs. However, constru

    Discovering dense subgraphs and understanding their relations is important. Peeling algorithms (k-core, k-truss, and nucleus decomposition) have been shown to be effective to locate many dense subgraphs. However, constru

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    Source URL: mmds-data.org

    Language: English - Date: 2016-06-23 15:50:48
    4The Publication List of Fan Chung 金芳蓉 Books: 1. Spectral Graph Theory, CBMS Lecture Series Number 92, AMS Publications, 1997, xii+207

    The Publication List of Fan Chung 金芳蓉 Books: 1. Spectral Graph Theory, CBMS Lecture Series Number 92, AMS Publications, 1997, xii+207

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    Source URL: www.math.ucsd.edu

    Language: English - Date: 2015-06-08 19:35:49
    5JMLR: Workshop and Conference Proceedings vol 40:1–30, 2015 Computational Lower Bounds for Community Detection on Random Graphs Bruce Hajek

    JMLR: Workshop and Conference Proceedings vol 40:1–30, 2015 Computational Lower Bounds for Community Detection on Random Graphs Bruce Hajek

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    Source URL: jmlr.org

    Language: English - Date: 2015-07-20 20:08:36
    6Nonlinear Graph Sparsification for SLAM Mladen Mazuran Gian Diego Tipaldi Luciano Spinello

    Nonlinear Graph Sparsification for SLAM Mladen Mazuran Gian Diego Tipaldi Luciano Spinello

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    Source URL: europa2.informatik.uni-freiburg.de

    Language: English - Date: 2014-10-22 05:13:51
    7Lecture 10: Graph Data Structures Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794–4400

    Lecture 10: Graph Data Structures Steven Skiena Department of Computer Science State University of New York Stony Brook, NY 11794–4400

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    Source URL: www3.cs.stonybrook.edu

    Language: English - Date: 2008-06-19 03:42:13
    8ON NOWHERE DENSE GRAPHS ˇ RIL ˇ AND PATRICE OSSONA DE MENDEZ JAROSLAV NESET Abstract. A set A of vertices of a graph G is called d-scattered in G if no two dneighborhoods of (distinct) vertices of A intersect. In other

    ON NOWHERE DENSE GRAPHS ˇ RIL ˇ AND PATRICE OSSONA DE MENDEZ JAROSLAV NESET Abstract. A set A of vertices of a graph G is called d-scattered in G if no two dneighborhoods of (distinct) vertices of A intersect. In other

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    Source URL: iti.mff.cuni.cz

    Language: English - Date: 2016-02-04 05:53:37
      9Efficient Densest Subgraph Computation in Evolving Graphs Alessandro Epasto∗ Silvio Lattanzi

      Efficient Densest Subgraph Computation in Evolving Graphs Alessandro Epasto∗ Silvio Lattanzi

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      Source URL: www.epasto.org

      Language: English - Date: 2015-07-21 16:42:36