IEEE

A Federated Learning-Based Data Augmentation Method for Privacy Preservation Under Heterogeneous Data

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...
IEEE

Toward Understanding Federated Learning over Unreliable Networks

Abstract: This paper studies the efficiency of training a statistical model among an edge server and multiple clients via Federated Learning (FL) – a machine learning method that preserves data ...
Journal of Medical Internet Research

Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance

This tutorial introduces a comprehensive, clinically oriented, and compliance-aware framework integrating federated learning (FL) and blockchain for secure and privacy-preserving health care analytics ...