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X-WR-CALNAME:On the Performance of Ranking Algorithms with Privacy Consider
 ations
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260812T090400Z
UID:tag:localist.com\,2008:EventInstance_49092613745323
DTSTART:20250404T150000Z
DTEND:20250404T160000Z
DESCRIPTION:Friday\, April 4\nSEC LL2.221 or Zoom (Passcode: 988031)\n11:00
 am - 12:00pm\n\n \n\nOn the Performance of Ranking Algorithms with Privacy
  Considerations\nMartina Cardone\, Assistant Professor\, University of Min
 nesota\n\n \n\nAbstract: Today\, ranking algorithms are of fundamental imp
 ortance and are used in a wide variety of applications\, such as recommend
 er systems and search engines. Broadly speaking\, the goal of a ranking al
 gorithm is to sort a dataset so that users are provided with accurate and 
 relevant results. Although modern ranking algorithms promise efficient mea
 ns of performing large-scale data processing\, there are numerous privacy 
 considerations that must not be overlooked.\nIn this talk\, we consider th
 e private ranking recovery problem\, which consists of recovering the rank
 ing/permutation of an input data vector from a noisy version of it. We aim
  to establish fundamental trade-offs between the performance of the estima
 tion task\, measured in terms of probability of error\, and the level of p
 rivacy that can be guaranteed when the noise mechanism consists of adding 
 artificial noise.\n\n \n\nSpeaker Bio: Martina Cardone received her Ph.D. 
 degree in electronics and communications from Télécom ParisTech (with wo
 rk done at Eurecom in Sophia Antipolis\, France) in 2015. She is currently
  an Assistant Professor with the Electrical and Computer Engineering Depar
 tment\, University of Minnesota (UMN). From July 2015 to August 2017\, she
  was a Postdoctoral Research Fellow with the Electrical and Computer Engin
 eering Department\, UCLA Henry Samueli School. Her main research interests
  are in estimation theory\, network information theory\, network coding\, 
 and wireless networks with a special focus on their capacity\, security\, 
 and privacy aspects. She is a recipient of the 2022 McKnight Land-Grant Pr
 ofessorship\, the NSF CAREER Award in 2021\, the NSF CRII Award in 2019\, 
 the Outstanding Ph.D. Award from Télécom ParisTech (Paris\, France)\, an
 d the Qualcomm Innovation Fellowship in 2014.
GEO:42.363197;-71.127278
LOCATION:Science and Engineering Complex (SEC)\, SEC LL2.221
SUMMARY:On the Performance of Ranking Algorithms with Privacy Consideration
 s
URL;VALUE=URI:https://events.seas.harvard.edu/event/on-the-performance-of-r
 anking-algorithms-with-privacy-considerations
CATEGORIES:Colloquia / Seminar / Lecture
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