预告抢先看!2019大数据与现代统计国际研讨会通知来了

2019大数据与现代统计国际研讨会（BDMS2019）将于2019年6月21-23日于华东师范大学中山北路校区召开，此次会议将围绕大数据和现代统计学的方法和应用，旨在推动国际统计学家之间的学术交流。 

BDMS2019将由华东师范大学和中国现场统计研究会共同主办，并由华东师范大学统计学院、中国现场统计研究会大数据统计分会、Statistical Theory and Related Fields 编辑部和统计与数据科学前沿理论及应用教育部重点实验室（筹）共同承办。

 会 议 主 题

大数据统计推断

大数据机器学习

大数据深度学习

贝叶斯统计

多参数分析、高维数据分析

金融统计、精算和风险管理

生物统计和生存分析

随机过程控制和可靠性工程

非参数和半参数统计

社会统计、抽样方法和实验设计

 会 议 议 程 

6月21日（14点至20点30分）	报到/付费  (逸夫楼大厅)
6月22日-6月23日	Opening Ceremony and Logistics Session I: Statistical learning Session II: Bayes models and analysis Session III: Nonparametric methods Session IV: Causal inference and missing data Session V: Design, treatments and tests Session VI:  Prediction, classification, and learning Session VII:  High dimension and large scale data Closing Remarks

 会议地址: 

上海普陀区中山北路3663号华东师范大学逸夫楼

 交通:  

地铁3，4，13号线金沙江路站下步行10分钟

 会议注册费:   

200美元(国内参会者: 人民币1200元 )，包括会议期间的餐饮费。

 参会报名:  

方法一：登录会议网站，点击“参会注册”，网上直接注册缴费（使用信用卡）；

方法二：下载参会报名表,并通过邮件发送至starf@ecnu.edu.cn ，会务组收到邮件后与你确认相关信息。

 联系方式:  

汤银才: yctang@stat.ecnu.edu.cn

赵   伟: starf@ecnu.edu.cn

 会议网站:  

http://bdms2019.ecnu.edu.cn/

 会 议 报 告

 

序号	报告人/单位	题目
1	Lee-Jen Wei (Keynote Speaker) Harvard University, USA	Translational Data Science
2	Jiahua Chen Yunnan University and University of British Columbia, Canada	Learning Finite Mixture Models by Minimum Wasserstein Distance Estimate
3	Ori Davidov University of Haifa, Israel	On the Design of Experiments with Ordered Treatments
4	Xinwei Deng Virginia Tech, USA	A New Look of Best Subset Selection for Sparse Ridge Regression from Chance-Constrained Programming
5	Alexander Goldenshluger University of Haifa, Israel	Nonparametric Estimation in Queueing Systems with Infinite Number of Servers
6	Zhuoqiong He University of Missouri-Columbia USA	Bayesian Smoothing Spline Model and Its Application in Current Population Survey
7	Jiming Jiang University of California, Davis, USA	On High-Dimensional Misspecified Mixed Model Analysis and Genome-Wide Association Study: Variance Estimation and Big Data
8	Bingyi Jing Hong Kong University of Science and Technology, China	Measuring Clustering Strength of Networks via Normalized Clustering Coefficient
9	Quefeng Li University of North Carolina, Chapel Hill, USA	Integrative Linear Discriminant Analysis with Guaranteed Error Rate Improvement
10	Faming Liang Purdue University, USA	Extended Stochastic Gradient MCMC Algorithms for Large-Scale Bayesian Computing
11	Huazhen Lin Southwestern University of Finance and Ecomomics, China	Robust and Efficient Estimation for the Treatment Effect in Causal Inference and Missing Data Problems
12	Nan Lin Washington University, St. Louis, USA	A Non-Randomized Multiple Testing Procedure for Large-Scale Heterogeneous Discrete Hypotheses Based on Randomized Tests
13	Danyu Lin University of North Carolina, USA	Variable Selection for Multiple Types of High-Dimensional Features with Missing Data
14	Yanyuan Ma Penn State University, USA	A Versatile Estimation Procedure without Estimating the Nonignorable Missingness Mechanism
15	Thuan Nguyen Oregon Health & Science University, USA	Classified Mixed Logistic Model Prediction
16	Yiyuan She Florida State University, USA	Slow-kill for Big Data Learning
17	Dongchu Sun University of Missouri-Columbia USA and ECNU, China	Bayesian Analysis of a Covariance Matrix and Low Rank Learning
18	Alexander Tsodikov University of Michigan, USA	A Dynamic Cure Model: Does Treatment of Second Cancer Affect Prostate Cancer Survival?
19	Lei Wang Nankai University	Efficient quantile regression estimation and variable selection for longitudinal data with nonignorable dropouts
20	Suojin Wang Texas A&M University, USA	Simultaneous Confidence Bands for the Error Distribution Function in Nonparametric Regression
21	Min-ge Xie Rutgers University, USA	Individualized Group Learning
22	Hailiang Yang University of Hong Kong, Hong Kong	Optimal Insurance Strategies: A Hybrid Deep Learning Markov Chain Approximation Approach
23	Ancha Xu Zhejiang Gongshang University, China	Bayesian Analysis of Bivariate Wiener Degradation Process
24	Menggang Yu University of Wisconsin, USA	Causal Inference with Many Covariates: A General Framework
25	Rongxian Yue Shanghai Normal University, China	D-Optimal Designs for the Heteroscedastic Berman's Model on an Arc
26	Chunming Zhang University of Wisconsin, USA	MaxICA with Augmented Genetic Algorithm and Application to EEG data
27	Song Zhang University of Texas Southwestern Medical Center, USA	A Bayesian Survival Model Based on Additive Regression Tree to Predict The Readmission Risk of Heart Failure Patients
28	Zhengjun Zhang University of Wisconsin-Madison, USA	Statistical Learning of The Worst Regional Smog Extremes with Dynamic Conditional Modeling
29	Hongtu Zhu DiDi AI Labs and University of North Carolina at Chapel Hill, USA	Dynamic Demand and Supply Network Analysis for Ride Sharing Business

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《Statistical Theory and Related Fields》

Statistical Theory and Related Fields（中文刊名《统计理论及其应用》）由华东师范大学与中国现场统计研究会合作主办并由华东师范大学与英国Taylor & Francis合作出版，是国内首家统计学领域英文学术期刊, 并于2017年8月份正式创刊。

Statistical Theory and Related Fields将推出有关学术会议及专题研究的专刊或专栏，录用和发表在大数据统计分析、贝叶斯统计、高维数据分析、金融统计、保险精算、生物统计、统计调查方法、实验设计、生存分析、风险管理、可靠性工程、多元分析、随机分析与极限理论及其应用、理论统计、非参数和半参数统计、应用统计等领域中的重要创新成果。

网址：

https://www.tandfonline.com/toc/tstf20/current 

编辑部地址：

上海中山北路3663号干训楼623室

联系人：

王善平

(spwang@library.ecnu.edu.cn)

赵伟

(wzhao@xb.ecnu.edu.cn)

转载自公众号“华东师大经管学部”

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