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Clément Canonne

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Conditional Sampling for Distribution TestingWorkshop on Local Algorithms (WoLA) 20242024-08-05
Shows that access to conditional samples yields testers whose query complexity is poly(1/ε) testers and largely domain-size independent, giving algorithms for…
Talk
Locally Private Histograms in All Privacy RegimesExtroverted Sublinear Algorithms 20242024-06-17
Shows that the standard bitwise randomized-response protocol RAPPOR already attains much better accuracy in the low-privacy (large ε) regime once analyzed with…
Talk on
Distribution Testing: Hypothesis Testing from Very Little (or Very Private) DataSublinear Algorithms Boot Camp 20242024-05-21
Overview of concrete results: distribution testing under total-variation needs Θ(√k/ε²) samples for uniformity, and common reductions let many identity tests…
Talk on
Testing and Learning Distributions Under Local Information ConstraintsSublinear Algorithms and Nearest-Neighbor Search2018-11-27
Study uses the simultaneous referee model with n players each getting one sample and limited by a family of channels W. Exact claims: centralized sample needs…
Talk on
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