研究方向
工作经历
2024.2-至今 探花视频
，助理教授
2020.9-2023.12 香港中文大学统计学系，博士后研究员
论文与出版物
S. Song, Y. Lin & Y. Zhou (2024). Semi-supervised inference for block-wise missing data without imputation, Journal of Machine Learning Research. In press.
S. Song, Y. Lin & Y. Zhou (2023). A general M-estimation theory in semi-supervised framework, Journal of the American Statistical Association. In Press. .
L. Shao, S. Song & Y. Zhou (2023). Optimal subsampling for large sample quantile regression with massive data, Canadian Journal of Statistics, 51(2): 420-33.
P. Liu, S. Song & Y. Zhou (2022). Semiparametric varying-coefficient additive hazard model for clustered failure time Data with frailty effects, Canadian Journal of Statistics, 50(2): 549-71.
S. Song, Y. Lin & Y. Zhou (2021). Linear expectile regression under massive data, Fundamental Research, 1: 574-85.
English
官方微信