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Huichen Li
Huichen Li
University of Illinois Urbana-Champaign
Bestätigte E-Mail-Adresse bei illinois.edu - Startseite
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Zitiert von
Zitiert von
Jahr
Detecting ai trojans using meta neural analysis
X Xu, Q Wang, H Li, N Borisov, CA Gunter, B Li
2021 IEEE Symposium on Security and Privacy (SP), 103-120, 2021
2752021
Qeba: Query-efficient boundary-based blackbox attack
H Li, X Xu, X Zhang, S Yang, B Li
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
1592020
Data poisoning attack against unsupervised node embedding methods
M Sun, J Tang, H Li, B Li, C Xiao, Y Chen, D Song
arXiv preprint arXiv:1810.12881, 2018
792018
Exploring adversarial robustness of multi-sensor perception systems in self driving
J Tu, H Li, X Yan, M Ren, Y Chen, M Liang, E Bitar, E Yumer, R Urtasun
arXiv preprint arXiv:2101.06784, 2021
632021
A machine learning approach to prevent malicious calls over telephony networks
H Li, X Xu, C Liu, T Ren, K Wu, X Cao, W Zhang, Y Yu, D Song
2018 IEEE Symposium on Security and Privacy (SP), 53-69, 2018
462018
Progressive-scale boundary blackbox attack via projective gradient estimation
J Zhang, L Li, H Li, X Zhang, S Yang, B Li
International Conference on Machine Learning, 12479-12490, 2021
202021
Nonlinear projection based gradient estimation for query efficient blackbox attacks
H Li, L Li, X Xu, X Zhang, S Yang, B Li
International conference on artificial intelligence and statistics, 3142-3150, 2021
192021
Compromised ACC vehicles can degrade current mixed-autonomy traffic performance while remaining stealthy against detection
G Gunter, H Li, A Hojjati, M Nice, M Bunting, CA Gunter, B Li, J Sprinkle, ...
arXiv preprint arXiv:2112.11986, 2021
52021
Nonlinear gradient estimation for query efficient blackbox attack
H Li, L Li, X Xu, X Zhang, S Yang, B Li
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
52021
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