eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees

Privacy protection has attracted increasing attention, and privacy concerns often prevent flexible data utilization. In most industries, data are distributed across multiple organizations due to privacy concerns. Federated learning (FL), which enables cross-organizational machine learning by communi...

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Hlavní autoři: Fuki Yamamoto, Seiichi Ozawa, Lihua Wang
Médium: Artigo
Jazyk:Inglês
Vydáno: IEEE 2022-01-01
Edice:IEEE Access
Témata:
Machine learning
privacy-preserving
gradient boosting
federated learning
decision tree
On-line přístup:https://ieeexplore.ieee.org/document/9761890/
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