Private Histograms in the Shuffle Model

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A Google TechTalk, presented by Albert Cheu, 2021/10/27
Privacy in ML Seminars - ABSTRACT: In this talk, I describe two of the (many) differentially private histogram protocols in the shuffle model literature. The shuffle model can be thought of as a relaxation of the local model where a service anonymizes communication between users and an analyzer. The first histogram protocol we consider has asymptotic error close to what is possible in the central model. The second demands only a constant number of messages from each user, so long as the number of users is above a small threshold. The second protocol's estimates are also robust to malicious users.

Speaker:
Dr. Albert Cheu (Georgetown University)




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