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UID:f983147e72cf0e7782f2807a311a36a2
CATEGORIES:Discrete Math
CREATED:20230914T090011
SUMMARY: A Random Graph Model for Clustering Graphs 
LOCATION:HILL 705
DESCRIPTION:<p><strong>Abstract</strong>:&nbsp;We introduce a random graph model for cl
 ustering graphs with a given degree sequence. Unlike many previous random g
 raph models, we incorporate clustering effects into the model. We show that
  random clustering graphs can construct graphs with a power-law expected de
 gree sequence, small diameter, and any desired clustering coefficient. Our 
 results follow from a general theorem on subgraph counts which may be of in
 dependent interest.&nbsp;</p>
CONTACT:Speaker: Nicholas Sieger   (UCSD)
DTSTAMP:20260827T011127
DTSTART;TZID=America/New_York:20230918T140000
DTEND;TZID=America/New_York:20230918T150000
SEQUENCE:0
TRANSP:OPAQUE
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