Statistical methods and applications.
Jin, H., Ma, Y. and Jiang, F.*, (2022). Matrix Completion with Covariate Information and Informative Missingness. Journal of Machine Learning Research, 23(180), pp.1-62.
Jiang, F.*, Jin, H., Gao, Y., Xie, X., Cummings, J., Raj, A.*, and Nagarajan, S.* (2022). Time-varying Dynamic Network Model for Dynamic Resting State Functional Connectivity in fMRI and MEG Imaging. NeuroImage, 254, 119131.
Jin, H. (student), Yin, G., Yuan, B., and Jiang, F.* (2022). Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences. Technometrics, 64(2), 177-186.
Wang, J., Shen, H. and Jiang, F., (2023). Robust Recommendation Via Social Network Enhanced Matrix Completion. Statistica Sinica, 33, pp.1-23.
Valdes, G., Friedman, J.H., Jiang, F. and Gennatas, E.D., (2021). Representational Gradient Boosting: Backpropagation in the Space of Functions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(12), pp.10186-10195.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H.*, and Wang, Y.* (2017). Artificial Intelligence in Healthcare: Past, Present and Future, Stroke and Vascular Neurology, 2(4), 230-243.
Jiang, F. and Ma, Y., 2022. Poisson regression with error corrupted high dimensional features. Statistica Sinica, 32, pp.2023-2046.
Jiang, F., Cheng, Q. (student), Yin, G., and Shen, H. (2020). Functional Censored Quantile Regression. Journal of the American Statistical Association, 115(530), 931-944.
Ma, Y., Jiang, F. and Henmi, M., 2020. Understanding and Utilizing the Linearity Condition in Dimension Reduction. Statistica Sinica, 30(2), pp.763-781.
Jiang, F., Baek, S., Cao, J., Ma, Y.* (2018). A Functional Single Index Model, Statistica Sinica, 30(2020) 303-324
Jiang, F., Tian, L., Fu, H., Hasegawa, T., and Wei, L. J.* (2019). Robust Alternatives to ANCOVA for Estimating the Treatment Effect via a Randomized Comparative Study. Journal of the American Statistical Association, 114(528), 1854-1864.
Jiang, F.*, Ma, Y., and Wei, Y. (2019). Sufficient Direction Factor Model and its Application to Gene Expression Quantitative Trait Loci Discovery. Biometrika, 106(2), 417-432.
Tian, L., Jiang, F., Hasegawa, T., Uno, H., Pfeffer, M., and Wei, L. J*. (2019). Moving Beyond the Conventional Stratified Analysis to Estimate an Overall Treatment Efficacy with the Data from a Comparative Randomized Clinical Study. Statistics in Medicine, 38(6), 917-932.
Jiang, F., Yin, G., and Dominici, F. (2019). Bayesian Model Selection Approach to Multiple ChangePoints Detection with Non-Local Prior Distributions. ACM Transactions on Knowledge Discovery from Data (TKDD), 13(5), 1-17.
Jiang, F.*, Yin, G., and Dominici, F. (2018). Bayesian Multiple Change Point Detection with Non-local Priors, Neural Information Processing Systems.
Jiang, F.*, Ma, Y., and Yin, G. (2018). Kernel-based Adaptive Randomization toward Balance in Continuous and Discrete Covariates. Statistica Sinica, 28(4), 2841-2856.
Jiang, F., and Haneuse, S*. (2017). A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data. Scandinavian Journal of Statistics, 44(1), 112-129.
Jiang, F.*, Ma, Y., and Jack Lee, J. (2017). A Second-order Semiparametric Method for Survival Analysis, with Application to an Acquired Immune Deficiency Syndrome Clinical Trial Study. Journal of the Royal Statistical Society: Series C (Applied Statistics), 66(4), 833-846.
Jiang, F., Ma, Y., and Wang, Y. (2015). Fused Kernel-spline Smoothing for Repeatedly Measured Outcomes in a Generalized Partially Linear Model with Functional Single Index. Annals of statistics, 43(5), 1929.
Jiang, F., Jack Lee, J., and Mueller, P. (2013). A Bayesian Decision-theoretic Sequential Response-adaptive Randomization Design. Statistics in medicine, 32(12), 1975-1994.