Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study

Background: Machine learning (ML) is now widely deployed in our everyday lives. Building robust ML models requires a massive amount of data for training. Traditional ML algorithms require training data centralization, which raises privacy and data governance issues. Federated learning (FL) is an app...

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Vydané v:	JMIR medical informatics Ročník 9; číslo 6; s. e26598
Hlavní autori:	Cha, Dongchul, Sung, MinDong, Park, Yu-Rang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Toronto JMIR Publications 01.06.2021
Predmet:	Classification Collaboration Colorectal cancer Datasets Laboratories Machine learning Neural networks Original Paper Patients Privacy Servers Variables
ISSN:	2291-9694, 2291-9694
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