no code implementations • 10 Oct 2023 • Rémy Chapelle, Bruno Falissard
Privacy and utility metrics were computed for each of the resulting synthetic datasets, which were further assessed using machine learning approaches. Results: Computed metrics showed a satisfactory level of protection against attribute disclosure attacks for each synthetic dataset, especially when the full framework was used.
no code implementations • 9 Feb 2018 • Louis Falissard, Guy Fagherazzi, Newton Howard, Bruno Falissard
These methods provide a framework to model complex, non-linear interactions in large datasets, and are naturally suited to the analysis of hierarchical data such as, for instance, longitudinal data with the use of recurrent neural networks.