A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Large-scale collection of contextual information is often essential in order to gather statistics, train machine learning models, and extract knowledge from data. The ability to do so in a privacy-preserving way -- i.e., without collecting fine-grained user data -- enables a number of additional computational scenarios that would be hard, or outright impossible, to realize without strong privacy guarantees. In this paper, we present the design and implementation of practical techniques forarXiv:1508.06110v3 fatcat:oqrtjnqvr5hzjjmqxcbpxruoiq