Younghyun Kim

Platform Design for Privacy-Preserving Federated Learning using Homomorphic Encryption : Wild-and-Crazy-Idea Paper

2024

Federated learning (FL) has been increasingly widely used for distributed and privacy-preserving machine learning (ML) environments, as the raw training data can stay local to clients while leveraging model updates from individual clients. Homomorphic encryption …