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Hengrui Jia
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2020 – today
- 2024
- [c8]Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot:
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. USENIX Security Symposium 2024 - [i8]Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic:
LLM Dataset Inference: Did you train on my dataset? CoRR abs/2406.06443 (2024) - 2023
- [c7]Papia F. Rozario
, Eleana Ruehmann, Tyler Pham, Tianqi Sun, Jacob Jensen, Hengrui Jia, Zhongyue Yu, Rahul Gomes
Deep Learning Patch-Based Approach for Hyperspectral Image Classification. eIT 2023: 458-463 - [c6]Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning is Currently More Broken Than You Think. EuroS&P 2023: 797-816 - [i7]Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot:
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. CoRR abs/2307.00310 (2023) - 2022
- [c5]Hengrui Jia, Hongyu Chen, Jonas Guan, Ali Shahin Shamsabadi, Nicolas Papernot:
A Zest of LIME: Towards Architecture-Independent Model Distances. ICLR 2022 - [c4]Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot:
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. USENIX Security Symposium 2022: 4007-4022 - [i6]Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot:
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. CoRR abs/2208.03567 (2022) - 2021
- [c3]Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot:
Machine Unlearning. SP 2021: 141-159 - [c2]Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning: Definitions and Practice. SP 2021: 1039-1056 - [c1]Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, Nicolas Papernot:
Entangled Watermarks as a Defense against Model Extraction. USENIX Security Symposium 2021: 1937-1954 - [i5]Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning: Definitions and Practice. CoRR abs/2103.05633 (2021) - [i4]Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot:
SoK: Machine Learning Governance. CoRR abs/2109.10870 (2021) - [i3]Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot:
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. CoRR abs/2110.11891 (2021) - 2020
- [i2]Hengrui Jia, Christopher A. Choquette-Choo, Nicolas Papernot:
Entangled Watermarks as a Defense against Model Extraction. CoRR abs/2002.12200 (2020)
2010 – 2019
- 2019
- [i1]Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot:
Machine Unlearning. CoRR abs/1912.03817 (2019)
Coauthor Index
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