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X-WR-CALNAME:Invariance in machine learning methods: What\, why\, and then?
  - Benjamin Bloem-Reddy\, Assistant Professor\, UBC
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TZID:America/Vancouver
TZUNTIL:20221106T090000Z
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DTSTART:20201101T020000
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
RDATE:20211107T020000
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DTSTART:20210314T020000
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DTSTAMP:20260430T211847Z
CLASS:PUBLIC
CREATED:20210323T185620Z
DESCRIPTION:Please register for this event here. Abstract: Statistical and 
 machine learning methods that incorporate appropriate symmetries have prov
 en hugely successful\, from exchangeable probability models and de Finetti
 's theorem in Bayesian statistics\, to convolutional neural networks and t
 heir extensions in deep learning. I will give an overview of the what and 
 the why\, with an emphasis on recent work and some open problems\, and loo
 k towards what might be next. Please register for this event here.
DTSTART;TZID=America/Vancouver:20210331T140000
DTEND;TZID=America/Vancouver:20210331T150000
LAST-MODIFIED:20210610T225458Z
LOCATION:Please register to receive the Zoom link
SUMMARY:Invariance in machine learning methods: What\, why\, and then? - Be
 njamin Bloem-Reddy\, Assistant Professor\, UBC
TRANSP:OPAQUE
URL:https://caida.ubc.ca/event/invariance-machine-learning-methods-what-why
 -and-then-benjamin-bloem-reddy-assistant
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