42 citations · 59 across the 15 of their papers we have counts for
3 papers · 1 filter
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Dimitris Stripelis, Hamza Saleem, Tanmay Ghai +8
Federated learning (FL) enables distributed computation of machine learning models over various disparate, remote data sources, without requiring to transfer any individual data to…
Scaling Neuroscience Research using Federated Learning
Dimitris Stripelis, Jose Luis Ambite, Pradeep Lam +1
The amount of biomedical data continues to grow rapidly. However, the ability to analyze these data is limited due to privacy and regulatory concerns. Machine learning approaches t…
Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings
Dimitris Stripelis, Jose Luis Ambite
There are situations where data relevant to machine learning problems are distributed across multiple locations that cannot share the data due to regulatory, competitiveness, or pr…