6 papers
ReMIA: a Powerful and Efficient Alternative to Membership Inference Attacks against Synthetic Data Generators
Davide Scassola, Andrea Coser, Sebastiano Saccani
Tabular data sharing under privacy constraints is increasingly important for research and collaboration. Synthetic data generators (SDGs) are a promising solution, but synthetic da…
Empirical Evaluation of Structured Synthetic Data Privacy Metrics: Novel experimental framework
Milton Nicolás Plasencia Palacios, Alexander Boudewijn, Sebastiano Saccani +6
Synthetic data generation is gaining traction as a privacy enhancing technology (PET). When properly generated, synthetic data preserve the analytic utility of real data while avoi…
A Sobering Look at Tabular Data Generation via Probabilistic Circuits
Davide Scassola, Dylan Ponsford, Adrián Javaloy +5
Tabular data is more challenging to generate than text and images, due to its heterogeneous features and much lower sample sizes. On this task, diffusion-based models are the curre…
Graph-Conditional Flow Matching for Relational Data Generation
Davide Scassola, Sebastiano Saccani, Luca Bortolussi
Data synthesis is gaining momentum as a privacy-enhancing technology. While single-table tabular data generation has seen considerable progress, current methods for multi-table dat…
Contrastive Learning-Based privacy metrics in Tabular Synthetic Datasets
Milton Nicolás Plasencia Palacios, Sebastiano Saccani, Gabriele Sgroi +2
Synthetic data has garnered attention as a Privacy Enhancing Technology (PET) in sectors such as healthcare and finance. When using synthetic data in practical applications, it is…
Zero-Shot Conditioning of Score-Based Diffusion Models by Neuro-Symbolic Constraints
Davide Scassola, Sebastiano Saccani, Ginevra Carbone +1
Score-based diffusion models have emerged as effective approaches for both conditional and unconditional generation. Still conditional generation is based on either a specific trai…