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Han Xu
Han Xu
Verifisert e-postadresse på msu.edu - Startside
Tittel
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Adversarial attacks and defenses in images, graphs and text: A review
H Xu, Y Ma, H Liu, D Deb, H Liu, J Tang, A Jain, K
International Journal of Automation and Computing (2020), 2020
6912020
Adversarial attacks and defenses on graphs
W Jin, Y Li, H Xu, Y Wang, S Ji, C Aggarwal, J Tang
KDD Explorations 22, 19-34, 2021
274*2021
Deeprobust: a platform for adversarial attacks and defenses
Y Li, W Jin, H Xu, J Tang
AAAI (2021), 2021
163*2021
To be robust or to be fair: Towards fairness in adversarial training
H Xu, X Liu, Y Li, A Jain, J Tang
International Conference on Machine Learning (2021), 2021
1612021
Adversarial attacks and defenses on graphs: A review and empirical study
W Jin, Y Li, H Xu, Y Wang, J Tang
arXiv preprint, 2020
1112020
Graph neural networks with adaptive residual
X Liu, J Ding, W Jin, H Xu, Y Ma, Z Liu, J Tang
NeurIPS (2021), 2021
522021
A comprehensive survey on trustworthy recommender systems
W Fan, X Zhao, X Chen, J Su, J Gao, L Wang, Q Liu, Y Wang, H Xu, ...
arXiv preprint, 2022
312022
Jointly attacking graph neural network and its explanations
W Fan, H Xu, W Jin, X Liu, X Tang, S Wang, Q Li, J Tang, J Wang, ...
International Conference on Data Engineering (2023), 2023
302023
Transferable unlearnable examples
J Ren, H Xu, Y Wan, X Ma, L Sun, J Tang
International Conference on Learning Representations (2023), 2022
292022
Diffusionshield: A watermark for copyright protection against generative diffusion models
Y Cui, J Ren, H Xu, P He, H Liu, L Sun, J Tang
arXiv preprint, 2023
272023
Deep adversarial canonical correlation analysis
W Fan, Y Ma, H Xu, X Liu, J Wang, Q Li, J Tang
SIAM international conference on data mining (2020), 2020
242020
Imbalanced adversarial training with reweighting
W Wang, H Xu, X Liu, Y Li, B Thuraisingham, J Tang
International Conference on Data Mining (2022), 2022
182022
Adversarial attacks and defenses: Frontiers, advances and practice
H Xu, Y Li, W Jin, J Tang
KDD Tutorial (2020), 2020
162020
Covariance-insured screening
K He, J Kang, HG Hong, J Zhu, Y Li, H Lin, H Xu, Y Li
Computational statistics & data analysis (2019), 2019
162019
Yet meta learning can adapt fast, it can also break easily
H Xu, Y Li, X Liu, H Liu, J Tang
SIAM International Conference on Data Mining (2021), 2021
132021
A selective overview of feature screening methods with applications to neuroimaging data
K He, H Xu, J Kang
Wiley Interdisciplinary Reviews: Computational Statistics (2019) 11, e1454, 2019
132019
A robust semantics-based watermark for large language model against paraphrasing
J Ren, H Xu, Y Liu, Y Cui, S Wang, D Yin, J Tang
NACCL Findings (2024), 2023
92023
Probabilistic categorical adversarial attack and adversarial training
H Xu, P He, J Ren, Y Wan, Z Liu, H Liu, J Tang
International Conference on Machine Learning (2023), 2023
72023
On the generalization of training-based chatgpt detection methods
H Xu, J Ren, P He, S Zeng, Y Cui, A Liu, H Liu, J Tang
arXiv preprint, 2023
52023
How does the Memorization of Neural Networks Impact Adversarial Robust Models?
H Xu, X Liu, W Wang, Z Liu, AK Jain, J Tang
KDD (2023), 2023
5*2023
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Artikler 1–20