o Chen, L. and Huang, J. Z., Sparse Reduced-Rank Regression with Covariance Estimation, 2013, Sparse Reduced-Rank Regression with Covariance Estimation, submitted.
o Chen, L., 2013, A Model-Free Variable Selection Procedure for Survival Data, under revision.
o Chen, L., Dou, W. W., and Qiao, Z., “Ensemble Subsampling for Imbalanced Multivariate Two-Sample Tests”, 2013, Journal of American Statistical Association, to appear. paper
o Tang, S., Chen, L.*, Tsui, K-W, Doksum, K., “Nonparametric Variable Selection in Classification: CATCH Algorithm, 2014, Computational Statistics & Data Analysis, Vol 72, pg. 158-175. *joint first author and correspondence author, paper.
o Chen, L. and Buja, A. "Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing ", 2013, Journal of Machine Learning Research, Vol. 14, pg. 1145-1173, paper.
o Chen, L. and Huang, J.Z., “Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection”, 2012, Journal of American Statistical Association, Vol. 107, No. 500; pg. 1533-1545, paper.
o Chawarska, K., Campbell, D., Chen, L., Shic, F., Klin, A., Chang, J., Early Generalized Overgrowth in Boys with Autism, Archives of General Psychiatry. 2011;68(10):1021-1031
o Chen, L. and Buja, A. "Local Multidimensional Scaling for Nonlinear Dimension Reduction, Graph Drawing and Proximity Analysis", 2009, the Journal of American Statistical Association, Vol. 104, No. 485; pg. 209, paper, supplemental materials.
o Buja, A., Swayne, D., Littman, M., Dean, N., Hofmann, H. and Chen, L. "Data Visualization with Multidimensional Scaling", 2008, the Journal of Computational and Graphical Statistics, Vol. 17, Iss. 2; pg. 444 [.pdf]
o Ye, S. and Chen, L. Multivariate Regression with Block-structured Predictors.
o Chawarska, K., Ye, S., and Chen, L., Latent Structure Analysis of Spontaneous Attention to Complex Social Scenes in Toddlers with Autism.
o Chen, L., Campbell, D., and Chang, J., Multidimensional Fused Lasso for Classification with Application to Autism Study Using Eye-tracking Data.