5 papers
Disjoint Generation of Synthetic Data
Anton Danholt Lautrup, Muhammad Rajabinasab, Tobias Hyrup +2
We propose a new framework for generating tabular synthetic datasets via disjoint generative models. In this paradigm, a dataset is partitioned into disjoint subsets that are suppl…
Achieving Hilbert-Schmidt Independence Under Rényi Differential Privacy for Fair and Private Data Generation
Tobias Hyrup, Emmanouil Panagiotou, Arjun Roy +3
As privacy regulations such as the GDPR and HIPAA and responsibility frameworks for artificial intelligence such as the AI Act gain traction, the ethical and responsible use of rea…
Sharing is CAIRing: Characterizing Principles and Assessing Properties of Universal Privacy Evaluation for Synthetic Tabular Data
Tobias Hyrup, Anton Danholt Lautrup, Arthur Zimek +1
Data sharing is a necessity for innovative progress in many domains, especially in healthcare. However, the ability to share data is hindered by regulations protecting the privacy…
FSDEM: Feature Selection Dynamic Evaluation Metric
Muhammad Rajabinasab, Anton D. Lautrup, Tobias Hyrup +1
Expressive evaluation metrics are indispensable for informative experiments in all areas, and while several metrics are established in some areas, in others, such as feature select…
SynthEval: A Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data
Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek +1
With the growing demand for synthetic data to address contemporary issues in machine learning, such as data scarcity, data fairness, and data privacy, having robust tools for asses…