Yu, G., Li, Q., Shen, D. and Liu, Y. (2019). Optimal Sparse Linear Prediction for Block-missing Multi-modality Data without Imputation. Journal of the American Statistical Association, in press.
Yu, G., Yin, L., Lu, S. and Liu, Y. (2019). Confidence Intervals for Sparse Penalized Regression with Random Designs. Journal of the American Statistical Association, in press.
Liu, J., Yu, G. and Liu, Y. (2019). Graph--based Sparse Linear Discriminant Analysis for High Dimensional Classification. Journal of Multivariate Analysis, in press.
Zhao, J., Yu, G. and Liu, Y. (2018). Assessing Robustness of Classification using Angular Breakdown Point. Annals of Statistics, 46(6B), 3362-3389.
Yu, G., Liu, Y. and Shen, D. (2016). Graph-guided Joint Prediction of Class Label and Clinical Scores for the Alzheimer's Disease. Brain Structure and Function, 221, 3787-3801.
Yu, G. and Liu, Y. (2016). Sparse Regression Incorporating Graphical Structure among Predictors. Journal of the American Statistical Association, 111, 707-720.
Huang, R., Yu, G., Wang, Z., Zhang, J. and Shi, L. (2013). Dirichlet Process Mixture Model for Document Clustering with Feature Partitioin. IEEE Transactions on Knowledge and Data Engineering, 25, 1748-1759.
Yu, G., Zou, C. and Wang, Z. (2012). Outlier Detection in the Functional Observations with Application to Profile Monitoring. Technometrics, 54, 308-318.