柏杨

发布者:严继臧发布时间:2019-04-01浏览次数:22455

姓  名:柏杨
职  称:教授

研究方向:纵向(函数型)数据分析;张量(非欧)数据分析;复杂数据分析中的机器学习方法与应用(迁移学习、隐私学习)

教授课程:数理统计、数据科学导论、函数型数据分析方法、理论与应用

E - mail:statbyang@mail.shufe.edu.cn;电话:65904624    





研究项目

序号项目名称项目编号项目来源起止时间项目经费
1“高维数据下模型结构的识别与选择”15ZZ035上海市教育委员会自然科学研究项目2015-20178万
2“复杂经济数据的建模与应用”
教育部创新团队项目2014-2016
3“基于二次推断函数和经验似然的纵向数据半参数建模及应用”11001162国家自然科学基金青年项目2011-201316万
4“基于二次推断函数及经验似然的纵向数据半参数建模”上海高校选拔培养优秀青年教师科研专项基金2011-20123万
5“纵向数据建模中几个新热点问题研究”11771268国家自然科学基金常规面上项目2018-202245万


研究领域


纵向(函数型)数据分析;张量(非欧)数据分析;复杂数据分析中的机器学习方法与应用(迁移学习、隐私学习)


教育经历
2005/09-2009/08
香港大学统计与精算学系博士
2002/09-2005/07
华东师范大学统计系硕士
1998/09-2002/07

华东师范大学统计系学士


工作经历

2009.9-2014.8  上海财经大学,统计与管理学院,助教授

2014.9-2025.7  上海财经大学,统计与管理学院,副教授

2025.8-至今   上海财经大学,统计与数据科学学院,教授


研究成果

统计理论与方法研究成果:

34. 秦彩红、柏杨*, 高维两样本投影检验,《数理统计与管理》,2025+。


33. 刘伟、段亮杰、柏杨*,因果推断下的A/B测试分组方法研究,《数理统计与管理》、2025+


32. Yang Bai, Yuan Le and Fan Zhou. Variable Selection with Reinforcement Learning. Accepted by Statistical Theory and Related Fields.


31. Yang Bai, Caihong Qin, Mengli Zhang and Huichen Zhu, Degrees of Freedom and Model Selection in Linear Models with Repeated Measurement Error. Communication in Mathematics and Statistics. 2025+


30. Yang Sui, Ting Li and Yang Bai. GENERALIZED TENSOR REGRESSION WITH INTERNAL VARIATION REGULARIZATION.  Statistica Sinica. 2025+


29. Bai, Yang, Qin, Caihong and Zhu, Huichen. Functional Two-Sample Test based on Projection. Statistica Sinica. 2025+


28. Qin, C., Xie, J., Li, T., & Bai, Y.An Adaptive Transfer Learning Framework for Functional Classification. Journal of the American Statistical Association, 2025,120 (550), 1201-1213


27. Ran, Hao and Bai, Yang. Partially fixed bayesian additive regression trees. Statistical Theory and Related Fields, 2024, 8(3), 232-242.


26. Wan, Ran and Bai, Yang. Communication-efficient distributed statistical inference on zero-inflated Poisson models. Statistical Theory and Related Fields, 2024, 8(2), 81-106.


25.Yuan Le, Yang Bai* and Guoyou Qin, Subgroup analysis of linear models with measurement error. Canadian Journal of Statistics. 2024, 52 (1), 26-42.


24. Sui Y, He X, Bai Y. Implicit regularization in over-parameterized support vector machine. Advances in Neural Information Processing Systems. 2024 Feb 13; 36.


23.Mengli Zhang, Lan Xue, Carmen D. Tekwe, Yang Bai and Annie Qu. Partially Functional Linear Quantile Regression with Measurement Errors. Statistica Sinica. 2023, 33:2257-2280.


22.刘高生, 柏杨,余平. 部分函数型线性空间自回归模型的假设检验. 数学学报, 2023, 66(2): 239-252.


21.Yuan Le, Fan Zhou and Yang Bai, Reinforced mixture learning. Neural Networks. 2023, 165, 175-184.


20. Rongjie Jiang, Liming Wang and Yang Bai*, Optimal model averaging estimator for multinomial logit models. Statistical Theory and Related Fields. 2022, page 227-240.


19. Yang Bai, Rongjie Jiang and Mengli Zhang, Optimal model averaging estimator for expectile regressions. Journal of Statistical Planning and Inference. 2022, 217, 204-223.


18. Mengli Zhang and Yang Bai*, On the Use of Repeated Measurement Errors in Linear Regression Models. Metrika. 2021, 84, 779-803.


17. Guoying Xu and Bai Yang*, Estimation of nonparametric additive models with high order spatial autoregressive errors. Canadian Journal of Statistics. 2021, 49(2),311-343.


16. Rongjie Jiang, Liming Wang and Bai Yang*, Optimal model averaging estimator for semi-functionalpartially linear models. Metrika. 2021, 84, 167-194.


15. Gaosheng Liu and Yang Bai, Statistical inference in functional semiparametric spatial autoregressive model. AIMS Mathematics. 2021, 6(10), 10890-10906.


14. Yiming Tang, Yang Bai and Tao Huang, Network Vector Autoregression with Individual Effects. Metrika. 2021, 84, 875-893.


13. 徐群芳、刘高生、柏杨. 具有自相关误差结构的面板数据部分线性单指标模型的统计推断. 中国科学. 2019, 49(6), 1-30.


12. Qu, Qunfang and Bai,Yang, Semiparametric statistical inferences for longitudinal data with nonparametric covariance modeling. Statistics. 2017, 51(6), 1280-1303


11. Chen, Yuping, Bai, Yang and Fung, W. K., Structural Identication and Variable Selection in High-Dimensional Varying-Coefficient Models. Journal of Nonparametric Statistics. 2017, 29 (2), 258-279


10. Ma, Hai Qiang, Bai Yang and Zhu, Z. Y., Dynamic Single-index Model for Functional Data. Science China Math, 2016, 59 (12), 2561–2584


9. Bai, Yang, Hu, J. H. and You, J. H., Panel Data Varying-Coefficient Partially Linear Models with Both Spatially and Time-Wise Correlated Errors. Statistica Sinica, 2015, 25 (2), 507-528


8. Bai, Yang, Li, Rui, Huang, J. and You, J. H., Semiparametric Longitudinal Model with Irregular Time Autoregressive Error Process. Statistica Sinica, 2015, 25 (1), 275-294


7. Chen, Y. P. and Bai, Yang, Correlation Structure Selection for Longitudinal Data Based on Varying-Coefficient Model. Chinese Journal of Applied Probability and Statistics (Chinese Version). 2014, 30 (2), 181-194


6. Xu, Q. F. and Bai, Yang, Efficient Estimation of Varying Coefficient Seemly Unrelated Regression Model. Acta Mathematicae Applicatae Sinica, English Series, 2014, Vol. 30, No.1, 119-144.


5. Qin G. Y., Bai Yang, and Zhu Z. Y., Robust empirical likelihood inference for the parametric component in a generalized partial linear model with longitudinal data. Journal of Multivariate Analysis, 2012, 105 (1), 32-44.


4. Bai Yang, Fung W. K. and Zhu Z. Y., Weighted empirical likelihood for generalized linear models with longitudinal data. Journal of Statistical Planning and Inference, 2010, 140 (11), 3446-3456.


3. Qin G. Y., Bai Yang and Zhu Z. Y., Robust empirical likelihood for longitudinal data. Statistics and Probability Letters, 2009, 79 (20), 2101-2108.


2. Bai Yang, Fung W. K. and Zhu Z. Y., Penalized quadratic inference functions for single-index models with longitudinal data. Journal of Multivariate Analysis, 2009, 100 (1), 152-161.


1. Bai Yang, Zhu Z. Y. and Fung W. K., Partial linear models for longitudinal data based on quadratic inference functions. Scandinavian Journal of Statistics, 2008, 35 (1), 104-118.


应用研究成果:


3. Zou, C., Ji, H., Cui, J. ... Bai, Yang et al. Preliminary study on AI-assisted diagnosis of bone remodeling in chronic maxillary sinusitis. BMC Med Imaging, 2024, 24:140.


2. Gan H. C., Bai Y., Wei, June , Why do people change routes? Impact of information services. Industrial Management & Data Systems, 2013, 113 (3), 403-422.


1. Gan, H. C. and Bai, Yang, The effect of travel time variability on route choice decision: a generalized linear mixed model based analysis. Transportation, 2014, Vol. 41, 339-350.


奖励,荣誉


1. 教育部2014年度高等学校科学研究优秀成果奖二等奖(第二单位,第三完成人)

2. 上海财经大学2010-2011学年优秀教学三等奖


社会工作


学术专业服务:

1、中国现场统计学会资源与环境统计分会常务理事,秘书长

2、多次为如下国际、国内期刊审稿:
Annals of Statistics,Biometrika,Statistica Sinica,Journal of Multivariate Analysis (JMVA),  Annals of Institute of Statistical Mathematics (AISM), Computational Statistics and Data Analysis (CSDA), Journal of Korean Statistical Society(JKSS), 应用数学学报, 应用概率统计。


社会服务(兼职):
1、欧美同学会上财分会副会长、秘书长;

2、上海市侨联青年总会理事

 

学术报告(2008年以来)


1.“High Dimensional Varying-Coefficient Models for Longitudinal Data with Covariates Measurement Errors and Missing Response”,invited speaker,1st International Conference on Econometrics and Statistics,June 13-18,2017,Hong Kong

2.“Sub-group Analysis of non-parametric regression functions with longitudinal data”,邀请报告,吉林大学2017年青年概率统计学者论坛会议,2017年4月14-16,吉林长春

3.“An improved estimator of linear model with repeated measurement erros”,邀请报告,中南财经政法大学2017年青年统计学家论坛会议,2017年3月24-25,武汉

4.“Structural Identification and Variable Selection in High-Dimensional Varying-Coefficient Models”,邀请报告,南开大学统计论坛,2016年11月11-12,天津

5.“Variable Selection in Modeling Longitudinal Data with Error-in-Variables and Dropouts”,邀请报告,2016华东师范大学魏宗舒青年统计学者研讨会,2016年5月21日至23日,华东师范大学,上海

6.“Structural Identification and Variable Selection in High-Dimensional Varying-Coefficient Models”,分会报告,2015年第九次全国生存分析和应用统计研讨会,2015年4月9日至11日,福建武夷学院,武夷山

7.“Semiparametric Longitudinal Model with Irregular Time Autoregressive Error Process”,Invited speaker, 2013 Youth Statistician Symposium in Dongnan University,Nanjing,China,September 18-19,2013

8.“Empirical likelihood and robust empirical likelihood inferences for longitudinal data”,中会报告,2011年统计与管理国际学术会议暨第五届资源与环境统计学会学术会议,2011年9月23日至25日,重庆理工大学,重庆

9.“Robust empirical likelihood inference for the parametric component in a generalized partial linear model with longitudinal data”,分会报告, 2010年中国概率统计学术年会,2010年10月21日至25日,南开大学,天津

10.“Penalized quadratic inference functions for single-index models with longitudinal data”,Contributed section,Joint Statistics Meeting 2008,Denver,USA,August 3-7 2008

11.“Partial linear models for longitudinal data”,Contributed section,7th World Congress in Probability and Statistics,National University of Singapore,Singapore,July 14-19 2008

12.“Modeling Longitudinal data with quadratic inference functions”,Contributed section,International Workshop on Scientific Computing-Models,Algorithm and Applications,University of Hong Kong,Hong Kong,August 13-25 2006

 

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