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DTSTART:20180311T070000
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DTSTART:20171105T060000
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UID:69b680b85a7e6
DTSTART;TZID=America/Toronto:20180809T100000
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TRANSP:TRANSPARENT
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/masters-thesi
 s-presentation-disentangled-representation
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 3102 Waterloo ON N2L 3G1 Canada
SUMMARY:Master’s Thesis Presentation: Disentangled Representation Learnin
 g\nfor Stylistic Variation in Neural Language Models
CLASS:PUBLIC
DESCRIPTION:Vineet John\, Master’s candidate\nDavid R. Cheriton School of
  Computer Science\n\nThis thesis tackles the problem of disentangling the 
 latent style and\ncontent variables in a language modelling context. This 
 involves\nsplitting the latent representations of documents by learning wh
 ich\nfeatures of a document are discriminative of its style and content\,\
 nand encoding these features separately using neural network models.
DTSTAMP:20260315T094944Z
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