Breaking the Communication-Privacy-Accuracy Trilemma

22 Jul 2020Wei-Ning ChenPeter KairouzAyfer Özgür

Two major challenges in distributed learning and estimation are 1) preserving the privacy of the local samples; and 2) communicating them efficiently to a central server, while achieving high accuracy for the end-to-end task. While there has been significant interest in addressing each of these challenges separately in the recent literature, treatments that simultaneously address both challenges are still largely missing... (read more)

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