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。主要研究方向为统计学习、图神经网络、联邦学习等。
刘史毓
/助理研究员
电子邮箱：liushiyu AT swufe.edu.cn
所获奖项与荣誉
主持科研项目
代表性论文
- 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., 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).
- 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.
- 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).