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SUMMARY:Computationally Efficient Nonparametric Testing - Guang Cheng (Pur
 due)
DTSTART:20170526T150000Z
DTEND:20170526T160000Z
UID:TALK71962@talks.cam.ac.uk
CONTACT:Quentin Berthet
DESCRIPTION:A recent trend of big data problems is to develop computationa
 lly efficient inferential methods that embed computational thinking into u
 ncertainty quantification. In this talk I will introduce two new classes o
 f nonparametric testing that scale well with large datasets. One class is 
 based on randomized sketches which can be implemented in one computer\, wh
 ile the other class requires parallel computing. Our theoretical contribut
 ion is to characterize the minimal computational cost that is needed to ac
 hieve testing optimality. The proposed methods are examined by simulated a
 nd real datasets.
LOCATION:MR12\, Centre for Mathematical Sciences\, Wilberforce Road\, Camb
 ridge.
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