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SUMMARY:Sketching methods - John Bradshaw
DTSTART:20161110T133000Z
DTEND:20161110T150000Z
UID:TALK68508@talks.cam.ac.uk
CONTACT:Yingzhen Li
DESCRIPTION:Sketching methods (or sometimes called streaming algorithms) a
 re useful when you want an approximate property of a dataset when the comp
 utation of its true value would take too long or use too much memory. In t
 his talk we give a brief overview of some of the most popular sketching me
 thods\, including: the Flajolet-Martin algorithm\, for estimating the card
 inality of a dataset\; the Bloom Filter for testing set membership and the
  Count-Min Sketch for estimating occurrences of each item. We will try to 
 provide examples of when these methods are useful and where they are used 
 in big data applications.\n\nThere is no need to read any material prior t
 o the meeting.
LOCATION:Engineering Department\, CBL Room 438
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