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DTSTART:20260329T030000
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DTSTART:20251026T020000
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DTSTAMP:20260424T170524Z
UID:69a9b2967650f821985802@ist.ac.at
DTSTART:20260326T113000
DTEND:20260326T123000
DESCRIPTION:Speaker: Bardiya Aryanfard\nAbstract: In the continual observat
 ion model of differential privacy\, problems are generally considered easy
  if they admit an additive error polylogarithmic in the stream length T an
 d the universe size n. Conversely\, problems that require additive error p
 olynomial in n and T are considered difficult. Recently\, Raskhodikova and
  Steiner (PODS 25) proved polynomial lower bounds on the additive error of
  many graph problems under fully dynamic edge differential privacy. This r
 aises a natural question: are these problems difficult even in the inserti
 ons-only model\, or does their hardness arise strictly from the fully dyna
 mic setting?We show that for many problems\, the former is true. We prove 
 polynomial lower bounds for a variety of these problems (e.g.\, maximum ma
 tching) in the insertions-only setting. We then extend our techniques to t
 he problem of estimating all symmetric norms simultaneously (SNE)\, provid
 ing the first polynomial lower bound for this problem.Based on joint work 
 with Monika Henzinger\, David Saulpic\, and A. R. Sricharan (https://arxiv
 .org/abs/2512.15981\, to appear in PODS 26)
LOCATION:Moonstone Bldg / Ground floor / Seminar Room C (I24.EG.030c)\, IST
 A
ORGANIZER:achaturv@ist.ac.at
SUMMARY:Bardiya Aryanfard: TCS Seminar - Improved Lower Bounds for Privacy 
 under Continual Release
URL:https://talks-calendar.ista.ac.at/events/6369
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