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cs.DS2024
Fingerprinting Codes Meet Geometry: Improved Lower Bounds for Private Query Release and Adaptive Data Analysis
Xin Lyu, Kunal Talwar
Fingerprinting codes are a crucial tool for proving lower bounds in differential privacy. They have been used to prove tight lower bounds for several fundamental questions, especia…
cs.DS2024★ 1 cited
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
Hilal Asi, Vitaly Feldman, Jelani Nelson +3
We study the problem of private vector mean estimation in the shuffle model of privacy where users each have a unit vector . We propose a new multi-mes…