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DTSTART:20200308T070000
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DTSTART:20191103T060000
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DTSTART;TZID=America/Toronto:20200804T090000
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/masters-thesi
 s-presentation-data-augmentation-text
LOCATION:Online 200 University Avenue West Waterloo ON N2L 3G1 Canada
SUMMARY:Master’s Thesis Presentation: Data Augmentation for Text\nClassif
 ication Tasks
CLASS:PUBLIC
DESCRIPTION:PLEASE NOTE: THIS MASTER’S THESIS PRESENTATION WILL BE GIVEN 
 ONLINE.\n\nDANIEL TAMMING\, MASTER’S CANDIDATE\n_David R. Cheriton Scho
 ol of Computer Science_\n\nThanks to increases in computing power and the 
 growing availability of\nlarge datasets\, neural networks have achieved st
 ate of the art results\nin many natural language processing (NLP) and comp
 uter vision (CV)\ntasks. These models require a large number of training e
 xamples that\nare balanced between classes\, but in many application areas
  they rely\non training sets that are either small or imbalanced\, or both
 . To\naddress this\, data augmentation has become standard practice in CV.
 \nThis research is motivated by the observation that\, relative to CV\,\nd
 ata augmentation is underused and understudied in NLP.
DTSTAMP:20260313T161315Z
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