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2020 – today
- 2024
[j2]Yizhou Wang
, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu:
SLA$^{{\text{2}}}$2P: Self-Supervised Anomaly Detection With Adversarial Perturbation. IEEE Trans. Knowl. Data Eng. 36(12): 9282-9293 (2024)- [j1]Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. 2024 (2024) - [c9]Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava:
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW 2024: 980-991 - [i8]Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi, Eleonora Kreacic, Vamsi K. Potluru:
Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing. CoRR abs/2405.13804 (2024) - [i7]Rongzhe Wei, Eli Chien, Pan Li:
Differentially Private Graph Diffusion with Applications in Personalized PageRanks. CoRR abs/2407.00077 (2024) - [i6]Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li:
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. CoRR abs/2410.08299 (2024) - 2023
- [i5]Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR abs/2310.15524 (2023) - [i4]Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava:
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR abs/2312.16784 (2023) - 2022
- [c8]Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu:
Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection. CIKM 2022: 4555-4559 - [c7]Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li:
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. NeurIPS 2022 - [i3]Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li:
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR abs/2207.11311 (2022) - 2021
- [i2]Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu:
SLA2P: Self-supervised Anomaly Detection with Adversarial Perturbation. CoRR abs/2111.12896 (2021) - 2020
- [c6]Yingchao Wu, Bo Dong, Qinghua Zheng, Rongzhe Wei, Zhiwen Wang, Xuanya Li:
A Novel Tax Evasion Detection Framework via Fused Transaction Network Representation. COMPSAC 2020: 235-244 - [c5]Jingyi An, Qinghua Zheng, Rongzhe Wei, Bo Dong, Xuanya Li:
NEUD-TRI: Network Embedding Based on Upstream and Downstream for Transaction Risk Identification. COMPSAC 2020: 277-286 - [c4]Jingyi An, Rongzhe Wei, Zhichao Zha, Bo Dong:
Dual Adversarial Networks for Land-Cover Classification. COMPSAC 2020: 394-399 - [i1]Rongzhe Wei, Fa Zhang, Bo Dong, Qinghua Zheng:
DWMD: Dimensional Weighted Orderwise Moment Discrepancy for Domain-specific Hidden Representation Matching. CoRR abs/2007.09312 (2020)
2010 – 2019
- 2019
- [c3]Rongzhe Wei, Qinghua Zheng, Bo Dong, Kuanzheng Yang, Huan He, Jianfei Ruan:
ABR-HIC: Attention Based Bidirectional RNN for Hierarchical Industry Classification. IEEE BigData 2019: 1527-1536 - [c2]Rongzhe Wei, Bo Dong, Qinghua Zheng, Xulyu Zhu, Jianfei Ruan, Huan He:
Unsupervised Conditional Adversarial Networks for Tax Evasion Detection. IEEE BigData 2019: 1675-1680 - [c1]Yingchao Wu, Qinghua Zheng, Yuda Gao, Bo Dong, Rongzhe Wei, Fa Zhang, Huan He:
TEDM-PU: A Tax Evasion Detection Method Based on Positive and Unlabeled Learning. IEEE BigData 2019: 1681-1686
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