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arXiv:2302.01326 [cs.LG]AbstractReferencesReviewsResources

Federated Analytics: A survey

Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr

Published 2023-02-02Version 1

Federated analytics (FA) is a privacy-preserving framework for computing data analytics over multiple remote parties (e.g., mobile devices) or silo-ed institutional entities (e.g., hospitals, banks) without sharing the data among parties. Motivated by the practical use cases of federated analytics, we follow a systematic discussion on federated analytics in this article. In particular, we discuss the unique characteristics of federated analytics and how it differs from federated learning. We also explore a wide range of FA queries and discuss various existing solutions and potential use case applications for different FA queries.

Comments: To appear in APSIPA Transactions on Signal and Information Processing, Volume 12, Issue 1
Journal: APSIPA Transactions on Signal and Information Processing, Volume 12, Issue 1, 2023
Categories: cs.LG, cs.CR
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