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SUMMARY:Resampling methods for networks - Liza Levina (Michigan)
DTSTART:20221027T160000Z
DTEND:20221027T170000Z
UID:TALK176060@talks.cam.ac.uk
CONTACT:HoD Secretary\, DPMMS
DESCRIPTION:With network data becoming ubiquitous in many applications\, m
 any models and algorithms for network analysis have been proposed\, yet me
 thods for providing uncertainty estimates are much less common. Bootstrap 
 and other resampling procedures - that is\, drawing observations repeatedl
 y at random from an already observed sample -  are an effective tool for e
 stimating uncertainty in classical statistical settings\, but resampling n
 etwork data is substantially more complicated. This talk will provide a br
 ief introduction to networks and modeling network data as random graphs\, 
 and then introduce several recent uses of resampling for network data. \n\
 nA wine reception in the central core\,  will follow the talk 
LOCATION:Centre for Mathematical Sciences MR2
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