IEEE

Privacy-Enhanced Federated Learning Algorithm Empowered by Blockchain and Game Theory

Abstract: Federated learning enables participants to collaboratively train a global model through distributed training without sharing raw data. However, this distributed training is vulnerable to ...
IEEE

Toward Fast Personalized Semi-Supervised Federated Learning in Edge Networks: Algorithm Design and Theoretical Guarantee

Abstract: Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Federated ...
University of Geneva

Precision medicine’s inevitable trajectory toward rare-disease-sized cohorts: implications for machine learning and deep learning

As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...