173 citations · 182 across the 2 of their papers we have counts for
2 papers
cs.CR2020★ 9 cited
Anonymizing Data for Privacy-Preserving Federated Learning
Olivia Choudhury, Aris Gkoulalas-Divanis, Theodoros Salonidis +4
Federated learning enables training a global machine learning model from data distributed across multiple sites, without having to move the data. This is particularly relevant in h…
cs.LG2019★ 173 cited
Differential Privacy-enabled Federated Learning for Sensitive Health Data
Olivia Choudhury, Aris Gkoulalas-Divanis, Theodoros Salonidis +4
Leveraging real-world health data for machine learning tasks requires addressing many practical challenges, such as distributed data silos, privacy concerns with creating a central…