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UID:20250924T040625EDT-918546ZZTF@132.216.98.100
DTSTAMP:20250924T080625Z
DESCRIPTION:Title: Counting communities in weighted SBM via semidefinite pr
 ogramming\n\nAbstract: We present the problem of community detection and o
 f estimating the number of communities in a weighted Stochastic Block Mode
 l (SBM) in the regime of diverging degrees. To obtain consistent estimator
 s\, our approach uses a universality result for semidefinite programming\,
  which we establish\, along with asymptotic knowledge of the eigenstructur
 e of a GOE random matrix. In addition\, we construct hypothesis tests able
  to distinguish between any two candidate numbers of communities in the gr
 aph. We point out that this application of semidefinite programming for bo
 th problems is new even for the well-studied case of the unweighted SBM.\n
DTSTART:20250925T153000Z
DTEND:20250925T163000Z
LOCATION:Room 920\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue 
 Sherbrooke Ouest
SUMMARY:Deborah Sampaio (91ÉçÇø) 
URL:/science/channels/event/deborah-sampaio-mcgill-367
 914
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