21 citations · 30 across the 4 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 1 cited
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model
Seok-Ju Hahn, Junghye Lee
Federated learning platforms are gaining popularity. One of the major benefits is to mitigate the privacy risks as the learning of algorithms can be achieved without collecting or…
cs.CR2020★ 1 cited
Secure and Differentially Private Bayesian Learning on Distributed Data
Yeongjae Gil, Xiaoqian Jiang, Miran Kim +1
Data integration and sharing maximally enhance the potential for novel and meaningful discoveries. However, it is a non-trivial task as integrating data from multiple sources can p…