Private Histograms in the Shuffle Model
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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