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UID:www.tcs.tifr.res.in/event/1634
DTSTAMP:20251106T044359Z
SUMMARY:User-level Locally Differentially Private Gaussian Mean Estimation
DESCRIPTION:Speaker: Malhar Ajit  Managoli (TIFR)\n\nAbstract: \nDifferenti
 al Privacy addresses the problem of releasing aggregate statistics of some
  dataset (e.g. mean) while preserving the privacy of users who contributed
  the data (usually involving adding noise). DP is used for example when re
 leasing census data. There might be situations where the users do not trus
 t the authority collecting the data. For such cases\, Locally Differential
 ly Private protocols have been developed\, wherein users only ever send no
 isy versions of their data to the central server\, instead of the server c
 ollecting the data\, processing it\, and then adding noise. In this talk\,
  I will present a protocol for estimating the mean of a Gaussian variable 
 in an LDP manner. Based on "Distributed Private Mean Estimation" by Girgis
 \, Data\, and Diggavi.\n
URL:https://www.tcs.tifr.res.in/web/events/1634
DTSTART;TZID=Asia/Kolkata:20251107T160000
DTEND;TZID=Asia/Kolkata:20251107T170000
LOCATION:A-201 (STCS Seminar Room)
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