Li Xiong

First name
Li
Last name
Xiong
Liu, R., Zeighami, S., Lin, H., Shahabi, C., Cao, Y., Takagi, S., … Xiong, L. (2023). Supporting Pandemic Preparedness with Privacy Enhancing Technology. In (p. 10). IEEE. http://doi.org/10.1109/TPS-ISA58951.2023.00014
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Zhang, J., Xia, H., Sun, Q., Liu, J., Xiong, L., Pei, J., & Ren, K. (2023). Dynamic Shapley Value Computation. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) (p. 14). http://doi.org/10.1109/ICDE55515.2023.00055
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Xie, H., Xiong, L., & Yang, C. (2023). Federated Node Classification over Graphs with Latent Link-type Heterogeneity. In WWW ’23: Proceedings of the ACM Web Conference 2023 (p. 11). http://doi.org/10.1145/3543507.3583471
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Zhang, J., Sun, Q., Liu, J., Xiong, L., Pei, J., & Ren, K. (2023). Efficient Sampling Approaches to Shapley Value Approximation. Proceedings of the ACM on Management of Data, 1(1), 24. http://doi.org/10.1145/3588728
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Zhang, M., Lin, H., Takagi, S., Cao, Y., Shahabi, C., & Xiong, L. (2023). CSGAN: Modality-Aware Trajectory Generation via Clustering-based Sequence GAN. In IEEE International Conference on Mobile Data Management (p. 10). IEEE. http://doi.org/10.1109/MDM58254.2023.00032
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Xia, H., Liu, J., Lou, J., Qin, Z., Ren, K., Cao, Y., & Xiong, L. (2023). Equitable Data Valuation Meets the Right to Be Forgotten in Model Markets. Proceedings of the VLDB Endowment, 16(11), 14. http://doi.org/10.14778/3611479.3611531
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Sun, Q., Li, X., Zhang, J., Xiong, L., Liu, W., Liu, J., … Ren, K. (2023). ShapleyFL: Robust Federated Learning Based on Shapley Value. In KDD ’23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (p. 13). http://doi.org/10.1145/3580305.3599500
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Zhang, S., Lou, J., Xiong, L., Zhang, X., & Liu, J. (2023). Closed-form Machine Unlearning for Matrix Factorization. In 32nd ACM International Conference on Information and Knowledge Management. Retrieved from https://par.nsf.gov/biblio/10448802
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Liu, J., , , Zhang, X., Xiong, L., & Qin, Z. (2023). MUter: Machine Unlearning on Adversarial Training Models. In International Conference on Computer Vision. Retrieved from https://par.nsf.gov/biblio/10448795
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Liu, J., Lou, J., Xiong, L., & Meng, X. (2023). Personalized Differentially Private Federated Learning without Exposing Privacy Budgets. In 32nd ACM International Conference on Information and Knowledge Management. Retrieved from https://par.nsf.gov/biblio/10448800
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