Domain Compression: A primitive for distributed inference under communication & privacy constraints

Domain Compression: A primitive for distributed inference under communication & privacy constraints

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United States Google TechTalks
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Published on ● Video Link: https://www.youtube.com/watch?v=Q_Kej3Ca5Tw


Duration: 18:08
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A Google TechTalk, 2020/7/30, presented by Jayadev Acharya, Cornell University
ABSTRACT: We present Domain Compression, a method for reducing the alphabet size of statistical problems. It is randomness efficient, which makes it particularly suitable in distributed settings with constraints such as privacy and communication. We illustrate the method with a distributed goodness-of-fit algorithm that is sample-, communication-,privacy-, and public randomness- optimal, all simultaneously.



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