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Data Augmentation in Natural Language Processing
Manage episode 298694732 series 2570898
This week’s guests are Steven Feng, Graduate Student and Ed Hovy, Research Professor, both from the Language Technologies Institute of Carnegie Mellon University. We discussed their recent survey paper on Data Augmentation Approaches in NLP (GitHub), an active field of research on techniques for increasing the diversity of training examples without explicitly collecting new data. One key reason why such strategies are important is that augmented data can act as a regularizer to reduce overfitting when training models.
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Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.
229 에피소드
Manage episode 298694732 series 2570898
This week’s guests are Steven Feng, Graduate Student and Ed Hovy, Research Professor, both from the Language Technologies Institute of Carnegie Mellon University. We discussed their recent survey paper on Data Augmentation Approaches in NLP (GitHub), an active field of research on techniques for increasing the diversity of training examples without explicitly collecting new data. One key reason why such strategies are important is that augmented data can act as a regularizer to reduce overfitting when training models.
Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.
Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.
229 에피소드
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