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SUMMARY:Statistical Asymptotics with Differential Privacy - Daniel Kifer (
 Pennsylvania State University)
DTSTART:20161209T111500Z
DTEND:20161209T120000Z
UID:TALK69407@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Differential privacy introduces non-ignorable noise into synth
 etic data and query answers. A proper statistical analysis must account fo
 r both the sampling noise in the data and the additional privacy noise. In
  order to accomplish this\, it is often necessary to modify the asymptotic
  theory of statistical estimators. In this talk\, we will present a formal
  approach to this problem\, with applications to confidence intervals and 
 hypothesis tests.
LOCATION:Seminar Room 1\, Newton Institute
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