Preserving data privacy in Machine Learning pipelines with Federated Learning
FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.
ARIES: Evaluation of a reliable and privacy-preserving European identity management framework
In book "Future Generation Computer Systems", Volume 102, 2020, Pages 409-425, ISSN 0167-739X.