Security for Data Privacy in Federated Learning with CUDA-Accelerated Homomorphic Encryption in XGBoost – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-21T20:30:26Z http://www.open-lab.net/blog/feed/ Ziyue Xu <![CDATA[Security for Data Privacy in Federated Learning with CUDA-Accelerated Homomorphic Encryption in XGBoost]]> http://www.open-lab.net/blog/?p=93870 2024-12-17T19:33:44Z 2024-12-18T21:30:00Z XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative...]]> XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative...

XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative training, NVIDIA has developed Federated XGBoost, an XGBoost plugin for federation learning. It covers vertical collaboration settings to jointly train XGBoost models across decentralized data sources, as well as horizontal histogram-based��

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