Graph

Results: 12817



#Item
211

The Gridiron Risk Model Aptible Gridiron uses a graph database to model information security risks, events or situations that have the potential to cause adverse impacts.

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Source URL: www.aptible.com

- Date: 2018-03-21 14:07:12
    212

    Efficient Register and Memory Assignment for Non-orthogonal Architectures via Graph Coloring and MST Algorithms Jeonghun Cho Yunheung Paek 

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    Source URL: www.cs.fsu.edu

    - Date: 2016-05-21 11:37:03
      213

      LIBCGRAPH(3) LIBCGRAPH(3) NAME libcgraph − abstract graph library

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      Source URL: graphviz.gitlab.io

      - Date: 2018-02-25 17:47:22
        214

        Feature Correspondence via Graph Matching: Models and Global Optimization Lorenzo Torresani1, Vladimir Kolmogorov2, and Carsten Rother1 1 Microsoft Research Ltd., Cambridge, UK, {ltorre, carrot}@microsoft.com

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        Source URL: www.cs.dartmouth.edu

        - Date: 2008-07-28 18:13:30
          215

          Efficient implementation of evaluation strategies via token-guided graph rewriting Koko Muroya Dan R. Ghica

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          Source URL: www.cs.ox.ac.uk

          - Date: 2017-09-09 06:01:35
            216

            TAO: Facebook’s Distributed Data Store for the Social Graph Nathan Bronson, Zach Amsden, George Cabrera, Prasad Chakka, Peter Dimov Hui Ding, Jack Ferris, Anthony Giardullo, Sachin Kulkarni, Harry Li, Mark Marchukov Dm

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            Source URL: www.usenix.org

            - Date: 2013-06-26 05:39:14
              217

              Representing Online Conversation Structure with Graphs: A New Corpus and Model Jonathan Kummerfeld jkk.name A conversation graph expresses


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              Source URL: nlp.berkeley.edu

              - Date: 2018-03-12 18:26:55
                218

                SHORTEST PATHS IN THE TOWER OF HANOI GRAPH AND FINITE AUTOMATA DAN ROMIK Abstract. We present efficient algorithms for constructing a shortest path between two configurations in the Tower of Hanoi graph, and for computin

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                Source URL: www.math.ucdavis.edu

                - Date: 2014-02-10 20:43:55
                  219

                  DeepGraph: Graph Structure Predicts Egonet Growth 1 Cheng Li1 , Xiaoxiao Guo2 , Qiaozhu Mei1,2 School of Information, University of Michigan, Ann Arbor, MI, USA

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                  Source URL: ls3.rnet.ryerson.ca

                  - Date: 2017-01-02 10:24:16
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