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cs.CR2025
CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning
Kaveen Hiniduma, Zilinghan Li, Aditya Sinha +2
Privacy-Preserving Federated Learning (PPFL) is a decentralized machine learning approach where multiple clients train a model collaboratively. PPFL preserves the privacy and secur…
cs.CR2024
Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
Ravi Madduri, Zilinghan Li, Tarak Nandi +3
The concept of a learning healthcare system (LHS) envisions a self-improving network where multimodal data from patient care are continuously analyzed to enhance future healthcare…