
| 刘史毓(助理研究员)研究领域:统计学习、图神经网络、联邦学习等 |
个人信息:
刘史毓,助理研究员
西南财经大学统计交叉创新研究院
电子邮箱:liushiyu AT swufe.edu.cn
简历:
2024年7月毕业于电子科技大学计算机科学与技术专业,获得工学博士学位。现为西南财经大学统计交叉创新研究院助理研究员。
主持项目:
2025.01-2025.12:中央高校基本科研业务费青年教师成长项目《面向隐私数据的可信建模方法与理论研究》
代表性论文:
Zeng, D., Xu, Z., Liu, S., Pan, Y., Wang, Q., & Tang, X. (2025). On the power of adaptive weighted aggregation in heterogeneous federated learning and beyond. International Conference on Artificial Intelligence and Statistics (AISTATS).
Luo, J., Chen, G., Zhang, Y., Liu, S., Wang, H., Yu, Y., ... & Xu, Z. (2025). Centaur: bridging the impossible trinity of privacy, efficiency, and performance in privacy-preserving transformer inference. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 22751-22770.
Liu, S., Shi, W., Lv, S., Zhang, Y., Wang, H., & Xu, Z. (2024). Meta-learning via PAC-Bayesian with data-dependent prior: generalization bounds from local entropy. International Joint Conferences on Artificial Intelligence (IJCAI).
Liu, S., Luo, J., Zhang, Y., Wang, H., Yu, Y., & Xu, Z. (2024). Efficient privacy-preserving Gaussian process via secure multi-party computation. Journal of Systems Architecture, 151, 103134.
Liu, S., Wei, L., Lv, S., & Li, M. (2023). Stability and generalization of lp-regularized stochastic learning for graph convolutional networks. International Joint Conferences on Artificial Intelligence (IJCAI).
Ai, Q., Liu, S., He, L., & Xu, Z. (2023). Stein variational gradient descent with multiple kernels. Cognitive Computation, 15, 672-682.
Ai, Q., He, L., Liu, S., & Xu, Z. (2022). ByPE-VAE: Bayesian pseudocoresets exemplar VAE. Neural Information Processing Systems (NeurIPS).
电话:86-028-87352207
地址:四川省成都市青羊区光华村街55号
邮编:610074
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