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cs.LG2026
FMCL: Class-Aware Client Clustering with Foundation Model Representations for Heterogeneous Federated Learning
Mahad Ali, Laura J. Brattain
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its performance deteriorates under statistical heterogeneity.…
cs.LG2025
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions
Gulsah Hancerliogullari Koksalmis, Bulent Soykan, Laura J. Brattain +1
Alzheimer's Disease (AD) is marked by significant inter-individual variability in its progression, complicating accurate prognosis and personalized care planning. This heterogeneit…
cs.LG2025
Fine-Tuning Foundation Models with Federated Learning for Privacy Preserving Medical Time Series Forecasting
Mahad Ali, Curtis Lisle, Patrick W. Moore +3
Federated Learning (FL) provides a decentralized machine learning approach, where multiple devices or servers collaboratively train a model without sharing their raw data, thus ena…