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SUMMARY:Sparse graphs using exchangeable random measures: Models\, propert
ies and applications - François Caron (Department of Statistics\, Univers
ity of Oxford)
DTSTART;VALUE=DATE-TIME:20191111T120000Z
DTEND;VALUE=DATE-TIME:20191111T130000Z
UID:https://talks.ox.ac.uk/talks/id/f9f19da2-620c-4a5e-9fe6-211327a00b7e/
DESCRIPTION:In the talk I will present the class of random graphs based on
exchangeable random measures. Such class allows to model networks which a
re either dense or sparse\, that is where the number of edges scales subqu
adratically with the number of nodes. For some values of its parameters\,
it generates scale-free networks with power-law exponent between 1 and 2.
I will present the general construction\, a representation theorem for suc
h construction due to Kallenberg\, and discuss its sparsity\, power-law an
d transitivity properties. Then I will introduce a specific model within t
his framework that allows to capture sparsity/heavy-tailed degree distribu
tions as well as latent overlapping community structure\, and a Markov cha
in Monte Carlo algorithm for posterior inference with this model. Experime
nts are done on two real-world networks\, showing the usefulness of the ap
proach for network analysis. \n\nBased on joint work with Emily Fox\, Adri
en Todeschini\, Xenia Miscouridou\, Judith Rousseau\, Francesca Panero.\nS
peakers:\nFrançois Caron (Department of Statistics\, University of Oxford
)
LOCATION:Mathematical Institute (L4)\, Woodstock Road OX2 6GG
URL:https://talks.ox.ac.uk/talks/id/f9f19da2-620c-4a5e-9fe6-211327a00b7e/
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DESCRIPTION:Talk:Sparse graphs using exchangeable random measures: Models\
, properties and applications - François Caron (Department of Statistics\
, University of Oxford)
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