2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Protecting Sensitive Data in Image Synthesis via PAC-Private Adaptation for Diffusion Models
Boming Miao, Tao Zhang, Netanel Raviv +3
Synthetic data are increasingly used as an alternative to sharing sensitive records. However, synthetic data generation does not guarantee privacy, as diffusion models trained or a…
SMOTE-DP: Improving Privacy-Utility Tradeoff with Synthetic Data
Yan Zhou, Bradley Malin, Murat Kantarcioglu
Privacy-preserving data publication, including synthetic data sharing, often experiences trade-offs between privacy and utility. Synthetic data is generally more effective than dat…
Adaptive Recruitment Resource Allocation to Improve Cohort Representativeness in Participatory Biomedical Datasets
Victor Borza, Andrew Estornell, Ellen Wright Clayton +4
Large participatory biomedical studies, studies that recruit individuals to join a dataset, are gaining popularity and investment, especially for analysis by modern AI methods. Bec…
Dataset Representativeness and Downstream Task Fairness
Victor Borza, Andrew Estornell, Chien-Ju Ho +2
Our society collects data on people for a wide range of applications, from building a census for policy evaluation to running meaningful clinical trials. To collect data, we typica…