Published papers

26. B Jiang, J Li and Q Yao (2023) Autoregressive networks. Journal of Machine Learning Research, To appear. 

25. Q Li, B Jiang and D Sun (2023) MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation. Journal of Machine Learning Research, 24 (134), 1-44.

24. J Chen, B Jiang, J Li (2023) Nonparametric instrument model averaging. Journal of Nonparametric Statistics, 1-22

23. HM Ng, B Jiang and KY Wong (2023) Penalized estimation of a class of single‐index varying‐coefficient models for integrative genomic analysis. Biometrical Journal, 65, 2100139

22. B Jiang, C Liu and CY Tang (2023) Dynamic covariance matrix estimation and portfolio analysis with high-frequency data. Journal of Financial Econometrics.

21. Q Wang, T Yan, B Jiang and C Leng (2022) Two-mode networks: inference with as many parameters as actors and differential privacy. Journal of Machine Learning Research. 292, 1-38.  

20. Y Fan, B Jiang, T Yan and Y Zhang (2022). Asymptotic theory in bipartite graph models with a growing number of parameters. Canadian Journal of Statistics.

19. H Fang, Y Chen, L Chen, W Yang and B Jiang (2022) Standardized Dempster’s non‐exact test for high dimensional mean vectors. Stat, e466.

18. X Yu, C Wang, Z Yang and B Jiang (2022) Tuning selection for two-scale kernel density estimators. Computational Statistics, 1-17.

17. C Wang, B Jiang and L Zhu (2020) Penalized interaction estimation for ultrahigh dimensional quadratic regression. Statistica Sinica, to appear.

16. B Jiang, Z Chen and C Leng (2020) Dynamic linear discriminant analysis in high dimensional space. Bernoulli, 26, 1234-1268.   

15.  N Zhao, Q Xu, ML Tang, B Jiang, Z Chen and H Wang (2020) High dimensional variable selection under multicollinearity. Stat. 9(1), p.e272.  

14. C Wang, B Jiang (2020) An efficient ADMM algorithm for high dimensional precision matrix estimation via penalized quadratic loss. Computational Statistics & Data Analysis, 142, 106812. 

13. B Jiang, R Song, J Li and D Zeng (2019) Rejoinder for "Entropy learning for dynamic treatment regimes". Statistica Sinica, 29, 1633-1710.  

12. B Jiang, R Song, J Li and D Zeng (2019) Entropy learning for dynamic treatment regimes (with discussions). Statistica Sinica, 29, 1633-1710.  

11. T Yan, B Jiang, SE Fienberg, C Leng (2019)  Statistical inference in a directed network model with covariates. Journal of the American Statistical Association, 114, 857-868. 

10. B Jiang, X Wang, C Leng (2019) A direct approach for sparse quadratic discriminant analysis. Journal of Machine Learning Research, 19 (31).

9. B Jiang, J Li (2018) Sample size determination for high dimensional parameter estimation with application to biomarker identification.  Computational Statistics & Data Analysis, 118, 54-65.

8. B Jiang, J Li, J Fine (2018) On two-step residual inclusion estimator for instrument variable additive hazards model.  Biostatistics & Epidemiology, 2, 47-60.

7. C Wang, B Jiang (2018) On the dimension effect of regularized linear discriminant analysis. Electronic Journal of Statistics, 12, 2709-2742.

6. X Xia, B Jiang, J Li, W Zhang (2016) Low-dimensional confounder adjustment and high-dimensional penalized estimation for survival analysis. Lifetime data analysis，22, 547-569.

5.  B Jiang, C Leng (2016) High dimensional discrimination analysis via a semiparametric model. Statistics & Probability Letters，110, 103-110.

4.  B Jiang (2015) An empirical estimator for the sparsity of a large covariance matrix under multivariate normal assumptions. Annals of the Institute of Statistical Mathematics， 67, 211-227.

3.  B Jiang (2013) Covariance selection by thresholding the sample correlation matrix. Statistics & Probability Letters，83, 2492-2498.

2. J Li, B Jiang, JP Fine (2013) Multicategory reclassification statistics for assessing improvements in diagnostic accuracy. Biostatistics, 14, 382-394.

1.  B Jiang, WL Loh (2012) On the sparsity of signals in a random sample. Biometrika，99, 915-928.

Conference proceedings

3. KH Lim, EP Lim, B Jiang, P Achananuparp (2016) Using online controlled experiments to examine authority effects on user behavior in email campaigns. Proceedings of the 27th ACM Conference on Hypertext and Social Media, 255-260.

2. KH Lim, EP Lim, B Jiang, P Achananuparp (2015) Online experiments of authority effects on user behavior in email campaigns. Proceedings of the 2015 International Conference on Computational Social Science (IC2S2'15). 

1. KH Lim, B Jiang, EP Lim, P Achananuparp (2014) Do you know the speaker?: an online experiment with authority messages on event websites. Proceedings of the 23rd International Conference on World Wide Web, 1247-1252.

Collaborative work

3. Yang, et al. (2023) How likely is septic shock to develop in a patient with Fournier's gangrene? A risk prediction model based on a 7-year retrospective study. Gastroenterology Report, 10, goac038.

2. Wang, et al. (2020) The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores.  PeerJ 8, e10018. 

1. L Singh, et al. (2015) Back to basics: a bilingual advantage in infant visual habituation. Child development 86 (1), 294-302.