Anonymizing Data for Privacy-Preserving Federated Learning

21 Feb 2020Olivia ChoudhuryAris Gkoulalas-DivanisTheodoros SalonidisIssa SyllaYoonyoung ParkGrace HsuAmar Das

Federated learning enables training a global machine learning model from data distributed across multiple sites, without having to move the data. This is particularly relevant in healthcare applications, where data is rife with personal, highly-sensitive information, and data analysis methods must provably comply with regulatory guidelines... (read more)

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