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BEGIN:VEVENT
SUMMARY:Making sense of sequence data: a Bayesian approach
DTSTART:20110418T110000
DTSTAMP:20260502T005410Z
UID:72f5a96a2a4f94b6437ae8cdec8ef76c16d5b548214a8b7fe0cd829c
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Sharon Goldwater\, University of Edinburgh\nSupervised mac
 hine learning approaches have led to huge advances in\nmany AI application
 s over the last 20 years\, yet there are many\ndomains where supervised tr
 aining data is scarce\, unavailable\, or\nprohibitively costly.  Therefore
 \, developing improved unsupervised\ntechniques is critical.  This talk wi
 ll focus on unsupervised\nlearning from sequence data\, and how ideas from
  Bayesian statistics\ncan be used to improve the latent structures that ar
 e identified. 
LOCATION:MEB110
STATUS:CONFIRMED
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