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X-WR-CALNAME:Meta-Learning - A Roadmap for Few-Shot Transfer Learning - Hug
 o Larochelle\, Research Scientist\, Google Brain
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TZUNTIL:20220313T100000Z
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DTSTART:20191103T020000
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RDATE:20201101T020000
RDATE:20211107T020000
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DESCRIPTION:Please register for this event here. Abstract: A lot of the rec
 ent progress on many AI tasks were enabled in part by the availability of 
 large quantities of labeled data for deep learning. Yet\, humans are able 
 to learn new concepts or tasks from as little as a handful of examples. Me
 ta-learning has been a promising framework for addressing the problem of g
 eneralizing from small amounts of data\, known as few-shot learning. In th
 is talk\, I’ll present an overview of the state of this research area. I'l
 l describe Meta-Dataset\, a new benchmark we developed to push further the
  development of few…
DTSTART;TZID=America/Vancouver:20200824T153000
DTEND;TZID=America/Vancouver:20200824T163000
LAST-MODIFIED:20210610T230249Z
LOCATION:Please register to receive the Zoom link
SUMMARY:Meta-Learning - A Roadmap for Few-Shot Transfer Learning - Hugo Lar
 ochelle\, Research Scientist\, Google Brain
TRANSP:OPAQUE
URL:https://caida.ubc.ca/event/meta-learning-roadmap-few-shot-transfer-lear
 ning-hugo-larochelle-research-scientist-google
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