• DocumentCode
    3739332
  • Title

    Latent Graph Inference and Validation

  • Author

    Ivan Brugere

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Illinois at Chicago, Chicago, IL, USA
  • fYear
    2015
  • Firstpage
    1494
  • Lastpage
    1495
  • Abstract
    Graphs are a fundamental model to describe complex statistical relationships over many scientific domains. In this context, graphs are commonly used to investigate relational phenomena which are not directly observable. Our work formulates a Latent Network Inference problem and develops inference methods in a common context for scientific applications where there is an absence of ground truth.
  • Keywords
    "Predictive models","Topology","Conferences","Data mining","Data models","Testing","Uncertainty"
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
  • Electronic_ISBN
    2375-9259
  • Type

    conf

  • DOI
    10.1109/ICDMW.2015.224
  • Filename
    7395846