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PRODID:-//Cornell U. Department of Computer Science//Brown Bag Seminar//EN
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SUMMARY:Brown bag: Andrew Wilson
DESCRIPTION:Title: How do we build models that learn?\nSpeaker: Andrew
	 Wilson\nAbstract: To answer scientific questions\, and reason about
	 data\, we must build models and perform inference within those models. 
	 But how should we approach model construction and inference to make the
	 most successful predictions?  How do we represent uncertainty and prior
	 knowledge?  How flexible should our models be?  Should we use a single
	 model\, or multiple different models?  Should we follow a different
	 procedure depending on how much data are available?\n\nIn this talk I
	 will present a philosophy for model construction\, grounded in
	 probability theory.  I will exemplify this approach for human learning\,
	 scalable kernel learning\, and deep learning.
LOCATION:Gates 122
UID:2017-03-28
STATUS:CONFIRMED
DTSTART:20170328T160000Z
DTEND:20170328T170000Z
LAST-MODIFIED:20170322T232644Z
ORGANIZER;CN=Jonathan Shi:http://www.cs.cornell.edu/~jshi/brownbag/
DTSTAMP:20260408T131740Z
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