| Machine unlearning L Bourtoule, V Chandrasekaran, CA Choquette-Choo, H Jia, A Travers, ... 2021 IEEE Symposium on Security and Privacy (SP), 141-159, 2021 | 640 | 2021 |
| Entangled watermarks as a defense against model extraction H Jia, CA Choquette-Choo, V Chandrasekaran, N Papernot 30th USENIX security symposium (USENIX Security 21), 1937-1954, 2021 | 235 | 2021 |
| On the necessity of auditable algorithmic definitions for machine unlearning A Thudi, H Jia, I Shumailov, N Papernot 31st USENIX Security Symposium (USENIX Security 22), 4007-4022, 2022 | 103 | 2022 |
| Proof-of-learning: Definitions and practice H Jia, M Yaghini, CA Choquette-Choo, N Dullerud, A Thudi, ... 2021 IEEE Symposium on Security and Privacy (SP), 1039-1056, 2021 | 86 | 2021 |
| A zest of lime: Towards architecture-independent model distances H Jia, H Chen, J Guan, AS Shamsabadi, N Papernot International Conference on Learning Representations, 2021 | 20 | 2021 |
| SoK: Machine learning governance V Chandrasekaran, H Jia, A Thudi, A Travers, M Yaghini, N Papernot arXiv preprint arXiv:2109.10870, 2021 | 20 | 2021 |
| Proof-of-learning is currently more broken than you think C Fang, H Jia, A Thudi, M Yaghini, CA Choquette-Choo, N Dullerud, ... 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 797-816, 2023 | 16* | 2023 |
| Attention, novelty preference and the visual paired comparison task M Eizenman, J Chung, MH Yu, H Jia, P Jiang Experimental eye research 183, 52-56, 2019 | 4 | 2019 |
| LLM Dataset Inference: Did you train on my dataset? P Maini, H Jia, N Papernot, A Dziedzic arXiv preprint arXiv:2406.06443, 2024 | 1 | 2024 |
| Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD A Thudi, H Jia, C Meehan, I Shumailov, N Papernot arXiv preprint arXiv:2307.00310, 2023 | | 2023 |
| Finding Private Bugs: Debugging Implementations of Differentially Private Stochastic Gradient Descent C Fang, H Jia, AS Shamsabadi, N Papernot | | |
Nicolas PapernotUniversity of Toronto and Vector Institute在 utoronto.ca 的电子邮件经过验证
