| Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data G Ganev, B Oprisanu, E De Cristofaro 39th International Conference on Machine Learning (ICML 2022), 6944-6959, 2022 | 44 | 2022 |
| On Utility and Privacy in Synthetic Genomic Data B Oprisanu, G Ganev, E De Cristofaro 29th Network and Distributed System Security Symposium (NDSS 2022), 2022 | 12* | 2022 |
| dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation S Mahiou, K Xu, G Ganev 8th ICML Workshop on Theory and Practice of Differential Privacy (TPDP 2022 …, 2022 | 5 | 2022 |
| On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against" Truly Anonymous Synthetic Data'' G Ganev, E De Cristofaro arXiv preprint arXiv:2312.05114, 2023 | 2 | 2023 |
| Understanding how Differentially Private Generative Models Spend their Privacy Budget G Ganev, K Xu, E De Cristofaro arXiv preprint arXiv:2305.10994, 2023 | 2 | 2023 |
| When Synthetic Data Met Regulation G Ganev 1st ICML Workshop on Generative AI and Law (GenLaw 2023), part of ICML 2023, 2023 | 1 | 2023 |
| DP-SGD vs PATE: Which Has Less Disparate Impact on GANs? G Ganev 3rd AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI 2022 …, 2022 | 1 | 2022 |
| Synthetic Generation of Data with Many to Many Relationships K Xu, G Ganev, E Joubert, R Davison, O Van Acker, L Robinson, ... GB Patent WO/2023/223,044, 2023 | | 2023 |
| On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise L Arthur, J Costello, J Hardy, W O'Brien, J Rea, G Rees, G Ganev 1st ICML Workshop on Challenges in Deployable Generative AI, part of ICML 2023, 2023 | | 2023 |
| Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation K Xu, G Ganev, E Joubert, R Davison, O Van Acker, L Robinson 11th International Conference on Learning Representations (ICLR 2023), 2023 | | 2023 |
Emiliano De CristofaroProfessor at University of California, RiversideVerified email at ucr.edu
