| Cronus: Robust and heterogeneous collaborative learning with black-box knowledge transfer H Chang, V Shejwalkar, R Shokri, A Houmansadr arXiv preprint arXiv:1912.11279, 2019 | 190 | 2019 |
| On the privacy risks of algorithmic fairness H Chang, R Shokri 2021 IEEE European Symposium on Security and Privacy (EuroS&P), 292-303, 2021 | 129 | 2021 |
| On adversarial bias and the robustness of fair machine learning H Chang, TD Nguyen, SK Murakonda, E Kazemi, R Shokri arXiv preprint arXiv:2006.08669, 2020 | 63 | 2020 |
| On the impact of machine learning randomness on group fairness P Ganesh, H Chang, M Strobel, R Shokri Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 26 | 2023 |
| Bias Propagation in Federated Learning H Chang, S Reza The Eleventh International Conference on Learning Representations (ICLR), 2023 | 22 | 2023 |
| Watermark Smoothing Attacks against Language Models H Chang, H Hassani, R Shokri arXiv preprint arXiv:2407.14206, 2024 | 1 | 2024 |
| Context-Aware Membership Inference Attacks against Pre-trained Large Language Models H Chang, AS Shamsabadi, K Katevas, H Haddadi, R Shokri arXiv preprint arXiv:2409.13745, 2024 | | 2024 |
| Efficient Privacy Auditing in Federated Learning H Chang, B Edwards, AS Paul, R Shokri 33rd USENIX Security Symposium (USENIX Security 24), 307-323, 2024 | | 2024 |
