Publications and Preprints

* stands for PhD students under my supervision.
# stands for alphabetical authorship.

  • Feng, L. and Yang, G.* (2023). "Deep Kronecker Network", Biometrika, accepted. [link][arXiv].

  • Wu, S.* and Feng, L. (2023). "Sparse Kronecker Product Decomposition: A General Framework of Signal Region Detection in Image Regression", Journal of Royal Statistical Society, series B (JRSSB), 85(3): 783-809. [link][arXiv].

  • Feng, L. and Wang, J. (2022). "Projected Robust PCA with Application to Smooth Image Recovery ", Journal of Machine Learning Research (JMLR), 23(249): 1-41. [link][arXiv].

  • Bi, X.#, Feng, L.#, Li, C#. and Zhang, H. (2021)." Modeling Pregnancy Outcomes through Sequentially Nested Regression Models", Journal of American Statistical Association (JASA), 117(538): 602-616. [link].

  • Feng, L., Bi, X. and Zhang, H. (2020). "Brain Regions Identified as Being Associated with Verbal Reasoning through the Use of Imaging Regression via Internal Variation.", Journal of American Statistical Association (JASA), 116(533):144-158. [link].

  • Feng, L. and Zhang, C.-H. (2019). "Sorted Concave Penalized Regression", Annals of Statistics (AoS), 47(6): 3069-3098. [link][arXiv].

  • Bi, X., Feng, L., Wang, S., Lin, Z., Li, T., Zhao, B., Zhu, H. and Zhang, H. (2019)." Common Genetic Variants Influence Human Cortical Brain Regions and Risk of Schizophrenia", Genetic Epidemiology, 1-11. [link].

  • Feng, L. and Dicker, L.H. (2018). "Approximate Nonparametric Maximum Likelihood Inference for Mixture Models via Convex Optimization", Computational Statistics & Data Analysis (CSDA), 122, 80-91. [link].

  • Feng, L., Ma, R. and Dicker, L.H. (2017). "Nonparametric Maximum Likelihood Approximate Message Passing", Information Sciences and Systems (CISS), 2017 51st Annual Conference on (pp. 1-6), IEEE. [link].