3 papers
cs.LG2026
Flower Hub: A Reproducible Benchmarking Platform for Federated Learning in Simulation and Deployment
Yan Gao, Mohammad Naseri, Javier Fernandez-Marques +19
Federated learning (FL) has emerged as a key approach for training models across decentralized data, yet benchmarking in FL remains difficult to reproduce, compare, and extend. Exi…
cs.LG2024
FedMAP: Personalised Federated Learning for Real Large-Scale Healthcare Systems
Fan Zhang, Daniel Kreuter, Carlos Esteve-Yagüe +11
Federated learning (FL) promises to enable collaborative machine learning across healthcare sites whilst preserving data privacy. Practical deployment remains limited by statistica…
cs.LG2023
Recent Methodological Advances in Federated Learning for Healthcare
Fan Zhang, Daniel Kreuter, Yichen Chen +10
For healthcare datasets, it is often not possible to combine data samples from multiple sites due to ethical, privacy or logistical concerns. Federated learning allows for the util…