| Mitigating membership inference attacks by self-distillation through a novel ensemble architecture X Tang, S Mahloujifar, L Song, V Shejwalkar, M Nasr, A Houmansadr, ... 31st {USENIX} Security Symposium ({USENIX} Security 22), 1433-1450, 2022 | 63 | 2022 |
| A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization A Panda, X Tang, S Mahloujifar, V Sehwag, P Mittal ICML 2024, 2024 | 14* | 2024 |
| Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation X Tang, R Shin, HA Inan, A Manoel, F Mireshghallah, Z Lin, S Gopi, ... ICLR 2024, 2024 | 11 | 2024 |
| Machine Learning with Differentially Private Labels: Mechanisms and Frameworks X Tang, M Nasr, S Mahloujifar, V Shejwalkar, L Song, A Houmansadr, ... Proceedings on Privacy Enhancing Technologies 4, 332-350, 2022 | 11 | 2022 |
| Effectively Using Public Data in Privacy Preserving Machine Learning M Nasr, S Mahloujifar, X Tang, P Mittal, A Houmansadr International Conference on Machine Learning, 25718-25732, 2023 | 7 | 2023 |
| Differentially Private Image Classification by Learning Priors from Random Processes X Tang, A Panda, V Sehwag, P Mittal NeurIPS 2023, 35855--35877, 2023 | 5 | 2023 |
| Private Fine-tuning of Large Language Models with Zeroth-order Optimization X Tang, A Panda, M Nasr, S Mahloujifar, P Mittal arXiv preprint arXiv:2401.04343, 2024 | 2 | 2024 |
| Differentially Private Generation of High Fidelity Samples From Diffusion Models V Sehwag, A Panda, A Pokle, X Tang, S Mahloujifar, M Chiang, JZ Kolter, ... ICML 2023 Workshop Challenges in Deployable Generative AI, 2023 | | 2023 |
