LIN, Yuanyuan 林媛媛

Position Associate Professor
Email ylin [at] cuhk.edu.hk
ORCiD 0000-0003-1293-1040
Phone Number 3943 7924
Fax Number 2603 5188
Address LSB 113
Homepage https://ylin-stat.github.io/

Academic Background

BSc (Sun Yat-sen University)

PhD (The Hong Kong University of Science and Technology)

Research Interest

Selected Publications

  • Han, R., Luo, L., Lin, Y. and Huang, J. (2023+). Online inference with debiased stochastic gradient descent. Biometrika, in press.
  • Song, S.,  Lin, Y. and Zhou, Y. (2023).  A general M-estimation theory in semi-supervised framework. Journal of the American Statistical Association. In press.
  • Jiao, Y., Shen, G., Lin, Y. and Huang, J. (2023). Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors. Annals of Statistics 51, 691-716.
  • Shen G., Chen, K., Huang J. and Lin, Y. (2023). Linearized maximum rank correlation estimation. Biometrika 110, 187-203.
  • Han, D., Huang, J., Lin, Y., Liu, L., Qu, L. and Sun, L. Q. (2023). Robust signal recovery for high-dimensional log-contrast models with compositional covariates. Journal of Business and Economic Statistics 41, 957-967.
  • Lin, Y., Xie, J., Han, R. and Tang, N. (2023). Post-selection inference for high-dimensional logistic regression under case-control design. Journal of Business and Economic Statistics 41, 624-635.
  • Shen G., Jiao, Y., Lin, Y. and Huang, J. (2022). Approximation with CNNs in Sobolev Space: with Applications to Classification. Advances in Neural Information Processing Systems 25, 2876-2888. (NeurIPS 2022, “Oral paper”).
  • Hao, M., Lin, Y., Liu, K. and Zhao, X. (2022). Penalized nonparametric likelihood-based inference for current status data model. Electronic Journal of Statistics 16, 3099-3134.
  • Han, D., Huang, J., Lin, Y. and Shen, G. (2022). Robust post-selection inference of high-dimensional mean regression with heavy-tailed asymmetric or heteroskedastic errors. Journal of Econometrics 230, 416-431.
  • Dai, L., Chen, K., Li, G. and Lin, Y. (2022). Metric learning via cross-validation. Statistica Sinica 32, 1701-1721.
  • Song, S., Lin, Y. and Zhou, Y. (2021). Linear expectile regression under massive data. Fundamental Research 1, 574-585.
  • Tang, W., Xie, J., Lin, Y. and Tang, N. (2021). Quantile correlation-based variable selection. Journal of Business and Economics Statistics 40, 1081-1093.
  • Wang, Z., Liu, X., Tang, W. and Lin, Y. (2021). Incorporating graphical structure of predictors in sparse quantile regression. Journal of Business and Economics Statistics 39, 783-792.
  • Xie, J., Lin, Y., Yan X. and Tang, N. (2020). Category-adaptive variable screening for ultra-high dimensional heterogeneous categorical data. Journal of the American Statistical Association 115, 747-760.
  • Chan H. M., Tang, W., Curl P., Lin, Y., Wan S. M. and Ho N. M. (2020). Doping control analysis of total arsenic in equine plasma. Drug Testing and Analysis 12, 1462-1469.
  • Hao, M., Lin, Y. and Zhao, X. (2020). Nonparametric inference of right censored data with smoothing splines. Statistica Sinica 30, 153-173.
  • Lin, Y., Liu, X. and Hao, M (2018). Model-free feature screening of high dimensional survival data. Science China Mathematics 61, 1617-1636. (Best Paper Award, Science China Mathematics, 2021).
  • Lin, Y., Luo, Y., Xie, S. and Chen, K. (2017). Robust estimation for general transformation models with random effects. Biometrika 104, 971-986.
  • Wong K. Y., Kwok W. H., Chan, H. M., Choi L. S., Ho N. M., Jaubert M., Bailly-Chouriberry L., Bonnaire Y., Cawley A., Williams H. M., Keledjian J., Brooks L., Chambers A., Lin, Y. and Wan S. M. (2017). Doping control study of AICAR in post-race urine and plasma samples from horses. Drug Testing and Analysis 9, 1363-1371.
  • Chen, K., Lin, Y., Yao, Y. and Zhou, C. (2017). Regression analysis with response-selective sampling. Statistica Sinica 27, 1699-1714.
  • Chen, K., Lin, Y., Wang, Z. and Ying, Z. (2016). Least product relative error regression. Journal of Multivariate Analysis 144, 91-98.
  • Lin, Y. and Chen, K. (2013). Efficient estimation of the censored linear regression model. Biometrika 100, 525-530.
  • Chen, K., Guo, S., Lin, Y. and Ying, Z. (2010). Least absolute relative error estimation. Journal of the American Statistical Association 105, 1104-1112.

Honors and Awards

  • Faculty Exemplary Teaching Award, The Chinese University of Hong Kong (2022)
  • Best Paper Award, Science China Mathematics (2021)
  • Vice-Chancellor’s Exemplary Teaching Award, The Chinese University of Hong Kong (2016)
  • Faculty Exemplary Teaching Award, The Chinese University of Hong Kong (2016)

Major Research Grants

2024-2026
General Research Fund (GRF), Hong Kong Research Grants Council
Project title: Deep generative approaches to semi-supervised classification.
2021-2023
General Research Fund (GRF), Hong Kong Research Grants Council
Project title: Semiparametric and nonparametric inference of survival data.
2020-2022
General Research Fund (GRF), Hong Kong Research Grants Council
Project title: Statistical analysis of distributed case-control studies.
2016-2019
General Research Fund (GRF), Hong Kong Research Grants Council
Project title: Statistical inference of quantile regression: flexible composite quantile regression and nearly semiparametric efficient estimation.
2013-2018
Early Career Scheme (ECS), Hong Kong Research Grants Council
Project title: Statistical inference for relative error-based regression: estimation and model selection.

Professional Activities

2022-2024
Member, Nominating and Election Committee, ICSA
2021-2022
Member, Scientific Program Committee, The 12th ICSA International Conference, 2022
2018-2019
Member, Scientific Program Committee, ICSA China 2019
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