报告题目：Scalable and Model-free Methods forMulticlass Probability Estimation
报 告 人：Helen Zhang教授美国亚利桑那尊龙凯时
报告时间：2019年7月11日上午9:00-9:40
报告地点：数学楼一楼第一报告厅
报告摘要:
Classicalapproaches for multiclass probability estimation are mostly model-based, suchas logistic regression or LDA, by making certain assumptions on the underlyingdata distribution. We propose a new class of model-free methods to estimateclass probabilities based on large-margin classifiers. The method is scalablefor high-dimensional data by employing the divide-and-conquer technique, whichsolves multiple weighted large-margin classifiers and then constructsprobability estimates by aggregating multiple classification rules. Withoutrelying on any parametric assumption, the estimates are shown to be consistentasymptotically. Both simulated and real data examples are presented toillustrate performance of the new procedure.
报告人简介：
Helen Zhang是美国亚利桑那尊龙凯时数学系，统计学跨学科和应用数学跨学科的教授。她于2002年从美国威斯康星尊龙凯时麦迪逊分校获得博士学位，2002年至2011年期间担任美国北卡罗来纳州立尊龙凯时的助理教授和副教授。她的主要研究方向包括非参数建模，统计机器学习，高维数据分析和应用的理论和方法。她目前是ISI journal Stat的主编。 她是美国统计学会和国际数学统计学会当选会员和2019年IMS Medallion lecture speaker。
报告题目：Learning ParameterHeterogeneity over Networks: A Distributed Tree-Based Fused-Lasso Approach
报 告 人：Zhengyuan Zhu教授美国爱荷华州立尊龙凯时
报告时间：2019年7月11日上午9:40-10:20
报告地点：数学楼一楼第一报告厅
报告摘要:
We propose an adaptive fused-lasso based coefficient subgroupapproach in the decentralized network system. The major goal is to improve themodel estimation efficiency by aggregating the neighbors & information aswell as identify the subgroup membership for each node in the network. In particular,a tree-based $l_1$ penalty is proposed to save the computation andcommunication cost. We also design a decentralized generalized alternatingdirection method of multiplier algorithm for solving the objective function inparallel. The theoretical properties are derived to guarantee both the modelconsistency and the algorithm convergence. Thorough numerical experiments arealso conducted to back up our theory, which also show that our approachoutperforms in the aspects of the estimation accuracy, computation speed andcommunication cost.
报告人简介：
Zhengyuan Zhu是美国爱荷华州立尊龙凯时LAS院长统计学教授，也是调查统计与方法学中心主任。他于2002年获得美国芝加哥尊龙凯时统计学博士学位，并于2009年加入没过过爱荷华州立尊龙凯时，之前他担任美国北卡罗来纳尊龙凯时教堂山分校统计学助理教授。他拥有空间统计，调查统计，空间抽样设计和时间序列分析方面的专业知识，并对环境统计，遥感，自然资源调查和农业统计中的应用感兴趣。他是许多国家大型纵向调查的PI和co-PI，包括美国国家资源调查，美国BLM管理土地调查和保护影响评估项目调查。
报告题目：Model averaging prediction for time series models witha divergingnumberof parameters
报 告 人：Guohua Zou教授首都师范尊龙凯时
报告时间：2019年7月11日上午10:40-11:20
报告地点：数学楼一楼第一报告厅
报告摘要:
Animportant problem with model averaging approach is the choice ofweights.In this paper, a generalized Mallows model averaging (GMMA) criterion forchoosingweights is developed in the context of an infinite order autoregressive(AR(infinity))process. The GMMA method adapts to the circumstances in which thedimensionsof candidate models can be large and increase with the sample size. TheGMMAmethod is shown to be asymptotically optimal in the sense of obtaining thebestout-of-sample mean-squared prediction error (MSPE) for both the independent-realizationand the same-realization predictions, which, as a byproduct, solves aconjecture put forward by Hansen (2008) that the well-known Mallows modelaveraging (MMA) criterion from Hansen (2007) is asymptotically optimal forpredicting the future of a times series. The rate of the GMMA based weightestimator tending to the optimal weight vector minimizing theindependent-realization MSPE is derived as well. Both simulation experiment andreal data analysis illustrate the merits of GMMA method in the prediction ofAR(infinity) process.
报告人简介：
Zou教授于1995年获得中国科学院系统科学研究所统计学博士学位。他获得国家杰出青年科学基金项目资助。 他的主要研究兴趣包括利用统计理论和方法来分析实际的经济，医学和遗传数据。他的研究领域包括统计模型选择和平均，调查抽样，统计决策理论和统计遗传学。他特别关注的是混合效应模型，预测试估计和计量经济学预测因子和测试的敏感性，估计量和预测因子的最优性，如可接受性和极小性，调查中的设计和数据分析，以及疾病和基因之间的联系和关联研究。
报告题目：How many people canthe Earth support?
报 告 人：Joel E. Cohen教授美国洛克菲勒尊龙凯时和哥伦比亚尊龙凯时，美国科学院院士
报告时间：2019年7月11日下午2:00-3:00
报告地点：数学楼一楼第二报告厅
报告摘要:
Historical estimates of how many people the Earth can support ranged from<109to >1030people. The estimates had widely differentassumptions, methods, and purposes. To make "How many people can the Earthsupport?" into a scientifically meaningful question requires at least 11 basicassumptions. Even with clear assumptions, estimates of how many people theEarth can support depend on interactions of populations, environments,economies, and cultures. These interactions are complex and poorly understood. Henceestimates of how many people the Earth can support are highly uncertain.
Although no oneknows how many people the Earth can support, people can do three kinds ofthings to make life better now and in the future: create a bigger pie (createand use new technologies), bring fewer forks to the table (slow populationgrowth and reduce the material throughput of consumption), and practice bettermanners (resolve conflicts peacefully, trade more efficiently, and govern lessviolently and less corruptly). Universal basic and secondary education would helpfuture generations do all three.Educationshould give children a good understanding of the workings of their own bodiesand minds and the bodies and minds of others.
Butchildren can learn only if their brains andbodies work well. Hence universal education requires good nutrition for all childrenand their mothers. Despite a global abundance of food, nearly a quarter ofchildren under 5 years old are stunted from chronic undernutrition andinfection. The reduction in later economic output when children become workersdue to malnutrition in childhood is far greater than the cost of feeding allchildren and their mothers well. Feeding and educating all children and theirmothers well is profitable economically and desirable morally.
报告人简介：
Joel E.Cohen是美国洛克菲勒尊龙凯时的Abby Rockefeller Mauzé教授和哥伦比亚尊龙凯时的教授。他和他的同事使用数学，统计和计算工具研究人口，生态系统和环境。 他的工作重点是影响人类健康的现象，人类与之相互作用的其他物种以及人类环境。最近的例子包括食物网，昆虫传播的感染，龙卷风和人口动态。Cohen使用模型来预测未来的人口增长，国际移民，生命以及教育与生育的相互作用。
Cohen教授在哈佛尊龙凯时接受教育，并获得了学士学位。以优异成绩，获得两个硕士学位和两个博士学位，一个是应用数学，另一个是人口科学和热带公共卫生。他一直在哈佛尊龙凯时任教，直到1975年，他加入洛克菲勒尊龙凯时，担任教授和人口实验室负责人。此外，自1995年以来，他一直是哥伦比亚尊龙凯时国际和公共事务学院的教授。他还隶属于哥伦比亚尊龙凯时地球与环境科学系及统计系。他在芝加哥尊龙凯时统计系有名誉任命。
他是美国国家科学院院士，美国艺术与科学学院院士，美国哲学学会会员。他获得过麦克阿瑟基金会奖学金，这一被称为“天才”的奖，以及古根海姆奖奖学金，日本科学促进会的奖学金。他分享了泰勒环境成就奖和华盛顿特区泛美卫生组织Fred L. Soper奖的成果，以供人们研究南美锥虫病。他曾在阿根廷，中国，英国，法国和日本担任名誉和访问学术任命。Cohen教授获得了人口委员会颁发的第一个Olivia Schieffelin Nordberg奖，以表彰他1995年出版的How Many People Can the Earth Support?他还编写或编辑了其他13本书，其中包括两本关于普及教育，一系列科学和数学笑话，绝对零重力以及430多篇科学论文和章节。
宣讲进行时丨尊龙凯时学习贯彻党...04-02
