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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Clustering Sparse Graphs - Sanghavi\, S (Universit
y of Texas at Austin)
DTSTART;TZID=Europe/London:20130814T100000
DTEND;TZID=Europe/London:20130814T104500
UID:TALK46640AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/46640
DESCRIPTION:Graph clustering involves the task of partitioning
nodes\, so that the edge density is higher within
partitions as opposed to across partitions. A nat
ural problem\, it represents a first step in a wid
e array of applications in network analysis\, comm
unity detection\, recommendation systems etc.\n\nA
classic and popular statistical setting for evalu
ating between different solutions to this problem
is the stochastic block model\, also referred to a
s the planted partition model. In this talk\, we p
resent a new algorithm for this problem\, which im
proves by polynomial factors over the performance
of all previous known algorithms. It is based on c
onvex optimization\, and draws a connection betwee
n this problem and a different field: high-dimensi
onal statistical inference.\n
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:Mustapha Amrani
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