no code implementations • 19 Feb 2024 • Florian van Daalen, Lianne Ippel, Andre Dekker, Inigo Bermejo
In this article, we explore the use of federated ensembles of Bayesian networks (FBNE) in a range of experiments and compare their performance with locally trained models and models trained with VertiBayes, a federated learning algorithm to train Bayesian networks from decentralized data.
1 code implementation • 31 Oct 2022 • Florian van Daalen, Lianne Ippel, Andre Dekker, Inigo Bermejo
For structure learning we adapted the widely used K2 algorithm with a privacy-preserving scalar product protocol.
no code implementations • 17 Dec 2021 • Florian van Daalen, Inigo Bermejo, Lianne Ippel, Andre Dekker
Privacy-preserving machine learning enables the training of models on decentralized datasets without the need to reveal the data, both on horizontal and vertically partitioned data.