173 citations · 183 across the 3 of their papers we have counts for
3 papers
Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge
Prithwish Chakraborty, James Codella, Piyush Madan +22
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability…
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…
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…