Legality of Cannabis by U.S. Jurisdiction

Authors
Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Guha Thakurta
Publication date
2017
Conference
Advances in Neural Information Processing Systems
Pages
2285-2293
Description
We present new practical local differentially private heavy hitters algorithms achieving optimal or near-optimal worst-case error--TreeHist and Bitstogram. In both algorithms, server running time is and user running time is , hence improving on the prior state-of-the-art result of Bassily and Smith [STOC 2015] requiring server time and user time. With a typically large number of participants in local algorithms ( in the millions), this reduction in time complexity, in particular at the user side, is crucial for the use of such algorithms in practice. We implemented Algorithm TreeHist to verify our theoretical analysis and compared its performance with the performance of Google's RAPPOR code.
Total citations
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Scholar articles
R Bassily, K Nissim, U Stemmer, A Guha Thakurta - Advances in Neural Information Processing Systems, 2017