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Differential privacy is a promising approach to privacy-preserving data analysis. It has been the subject of a decade of intense scientific study, and has now been deployed in products at government agencies such as the U.S. Census Bureau and companies like Microsoft, Apple, and Google. MIT Technology Review named differential privacy one of 10 breakthrough technologies of 2020.Since data privacy is a pervasive concern, differential privacy has been studied by researchers from many distinct communities, including machine learning, statistics, algorithms, computer security, cryptography, databases, data mining, programming languages, social sciences, and law. We believe that this combined effort across a broad spectrum of computer science is essential for differential privacy to realize its full potential. To this end, our workshop will stimulate discussion among participants about both the state-of-the-art in differential privacy and the future challenges that must be addressed to make differential privacy more practical.
Fri 6:00 a.m. - 6:05 a.m.
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Opening Remarks
SlidesLive Video » Welcome by chairs Gautam Kamath and Audra McMillan |
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Fri 6:05 a.m. - 6:45 a.m.
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Low-Communication Algorithms for Private Federated Data Analysis
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Keynote Talk
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SlidesLive Video » Plenary talk by Kunal Talwar |
Kunal Talwar 🔗 |
Fri 6:45 a.m. - 7:00 a.m.
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Query Release via the Johnson Lindenstrauss Lemma
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Spotlight Talk
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SlidesLive Video » |
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Fri 7:00 a.m. - 7:30 a.m.
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Break
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Fri 7:30 a.m. - 9:00 a.m.
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Poster Session 1
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Poster Session
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List of posters on workshop website https://tpdp.journalprivacyconfidentiality.org/2022/ |
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Fri 9:00 a.m. - 10:30 a.m.
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Lunch
Lunch break |
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Fri 10:30 a.m. - 11:10 a.m.
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Private Mean Estimation with Connections to Robustness
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Keynote Talk
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SlidesLive Video » Plenary talk by Lydia Zakynthinou |
Lydia Zakynthinou 🔗 |
Fri 11:10 a.m. - 11:25 a.m.
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Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases
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Spotlight Talk
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SlidesLive Video » |
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Fri 11:25 a.m. - 11:40 a.m.
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Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It
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Spotlight Talk
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SlidesLive Video » |
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Fri 11:40 a.m. - 12:00 p.m.
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Prerecorded Talks 1
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Prerecorded Talks
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SlidesLive Video » |
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Fri 12:00 p.m. - 12:25 p.m.
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Break
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Fri 12:25 p.m. - 12:45 p.m.
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Prerecorded Talks 2
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Prerecorded Talks
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SlidesLive Video » |
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Fri 12:45 p.m. - 1:00 p.m.
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Private Convex Optimization via Exponential Mechanism
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Spotlight Talk
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SlidesLive Video » |
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Fri 1:00 p.m. - 1:15 p.m.
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The Price of Differential Privacy under Continual Observation
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Spotlight Talk
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SlidesLive Video » |
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Fri 1:15 p.m. - 1:30 p.m.
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Unlocking High-Accuracy Differentially Private Image Classification through Scale
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Spotlight Talk
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SlidesLive Video » |
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Fri 1:30 p.m. - 3:00 p.m.
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Poster Session 2
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Poster Session
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Author Information
Gautam Kamath (University of Waterloo)
Audra McMillan (Apple)
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