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SUMMARY:Differential Privacy Tutorial - Alex Matthews and John Bradshaw\, 
 University of Cambridge
DTSTART:20170309T133000Z
DTEND:20170309T150000Z
UID:TALK71562@talks.cam.ac.uk
CONTACT:Alexander Matthews
DESCRIPTION:Abstract:\n\nDifferential privacy is the dominant theory of st
 atistical analysis under constraints of individual privacy preservation. I
 n the first section\, which will constitute the majority of the talk\, we 
 will introduce the basic concepts of Differential Privacy and its motivati
 on. It will be similar to the first chapters of\n\n1) The Algorithmic Foun
 dations of Differential Privacy. Dwork and Roth. 2014\n\nHowever\, since o
 ur talk is introductory in nature no prior reading will be necessary.\n\nT
 o give a flavour of recent research\, we will then give a brief overview o
 f two recent papers on the topic specifically:\n\n2) Deep Learning with Di
 fferential Privacy. Abadi et al. 2016\n\n3) Differential Privacy For Funct
 ions and Functional Data. Hall et al. 2013
LOCATION:CBL Room BE-438\, Department of Engineering
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