12 citations · 21 across the 6 of their papers we have counts for
3 papers · 1 filter
Federated Bayesian Network Ensembles
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Ensemble-based learning works by t…
VertiBayes: Learning Bayesian network parameters from vertically partitioned data with missing values
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are probabilistic graphical models that have been widely used in art…
Privacy-Preserving Generalized Linear Models using Distributed Block Coordinate Descent
Erik-Jan van Kesteren, Chang Sun, Daniel L. Oberski +2
Combining data from varied sources has considerable potential for knowledge discovery: collaborating data parties can mine data in an expanded feature space, allowing them to explo…