BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:Probability Seminar
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260515T140214Z
UID:tag:localist.com\,2008:EventInstance_49277098826110
DTSTART:20250407T201500Z
DTEND:20250407T211500Z
DESCRIPTION:Speaker: Youngtak Sohn (Brown)\n\nTitle: Stochastic Block Model
  with Many Communities\n\nAbstract:\n\nThe stochastic block model (SBM)\, 
 a random graph generalizing the Erdős–Rényi model\, has long served as
  a framework for community detection. For SBMs with $n$ vertices and a fix
 ed number of communities $q$\, Decelle et al. (2011) predicted that effici
 ent recovery is possible above the Kesten–Stigum (KS) threshold and impo
 ssible below it. We review recent progress toward proving this conjecture.
  We then turn to the case where $q = q_n$ grows with $n$\, a setting for w
 hich no prediction currently exists. We show that the KS threshold can be 
 surpassed efficiently when $q_n \\gg \\sqrt{n}$\, while low-degree algorit
 hms fail to beat the KS threshold when $q_n \\ll \\sqrt{n}$. Based on join
 t work with Byron Chin\, Elchanan Mossel\, and Alex Wein.
GEO:42.358262;-71.090045
LOCATION:Building 2\, 143
SUMMARY:Probability Seminar
URL;VALUE=URI:https://calendar.mit.edu/event/probability-seminar-Youngtak-S
 ohn
CATEGORIES:Conferences/Seminars/Lectures
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