报告题目：Finite horizon semi-Markov games under the probability criterion
报 告 人：郭先平
工作单位：中山大学
报告时间：2023-08-07 8:30-11:30
报告地点：bat365在线平台网站3401
报告摘要：
This talk is on a two-person zero-sum game for finite horizon semi-Markov processes, where the concerned criterion is the probability that the total payoff produced by a system during a finite horizon exceeds a prescribed goal. which can be regarded as the security probability for player 1 as well as the risk probability for player 2. First, we give the characterization of the probability, and establish the Shapley equation and the existence of a saddle point under a suitable condition. Then, we develop a value iterative algorithm to compute an epsilon-saddle point and the value of the game by solving a series of matrix games. Finally, we demonstrate the application of our main results by an example on an inventory system.
报告人简介：
国家杰出青年科学基金获得者， 1996年于中南大学获博士学位，2002于中山大学晋升为教授，2003年入选教育部优秀青年教团队助计划，2004年入选教育部新世纪优秀人才支持计划，2010年被评为珠江学者特聘教授， 2018年被选为全国概率统计学会副理事长。担（曾）任国际（SCI）杂志 Advances in Applied Probability，Journal of Applied Probability，Science China Mathematics，Journal of Dynamics and Games，及国内期刊《中国科学：数学》、《应用数学学报》、《应用概率统计》等杂志编委。研究兴趣为马氏决策过程、随机博弈等。
报告题目：Testing high-dimensional covariate effects in the presence of covariate heterogeneity
报 告 人：朱利平
工作单位：中国人民大学
报告时间：2023-08-07 15:00-18:00
报告地点：bat365在线平台网站3401
报告摘要：
In this talk, I introduce several tests for the mean effects of high-dimensional covariates on the response. In many applications, different components of covariates usually exhibit various levels of variation, which is ubiquitous in high-dimensional data. To simultaneously accommodate such heteroscedasticity and high dimensionality, we propose a novel test based on an aggregation of the marginal cumulative covariances, requiring no prior information on the specific form of regression models. Our proposed test statistic is scale-invariance, tuning-free and convenient to implement. The asymptotic normality of the proposed statistic is established under the null hypothesis. We further study the asymptotic relative efficiency of our proposed test with respect to the state-of-art universal tests in two different settings: one is designed for high-dimensional linear model and the other is introduced in a completely model-free setting. A remarkable finding reveals that, thanks to the scale-invariance property, even under the high-dimensional linear models, our proposed test is asymptotically much more powerful than existing competitors for the covariates with heterogeneous variances while maintaining high efficiency for the homoscedastic ones.
报告人简介：
中国人民大学杰出学者特聘教授，统计与大数据研究院经理、教授、博士生导师。长期从事大数据统计学基础理论研究，研究领域包括高维及超高维数据分析、非线性相依数据分析等。入选国家高层次人才计划，获得国家杰出青年科学基金支持。受邀担任《统计年刊》、《多元统计分析》等多个国际国内学术期刊编委、副主编或领域主编。现任中国现场统计研究会高维数据统计分会和生存分析分会副理事长。
报告题目：Convergence of random variables under sub-linear expectations
报 告 人：张立新
工作单位：浙江大学
报告时间：2023-08-08 8:30-11:30
报告地点：bat365在线平台网站3401
报告摘要：
In this talk, we consider the weak and strong convergence of random variables under Peng's framework of sub-linear expectations. We will give sufficient and necessary conditions for the central limit theorem and functional central limit theorem. We show that if the sub-linear expectation space is rich enough, it will have no continuous capacity. A new Borel-Cantelli lemma is established under a popular regular condition on the sub-linear expectation and sufficient and necessary conditions are given for strong law of large numbers.
报告人简介：
浙江大学求是特聘教授。1995年获复旦大学理学博士学位， 1997年晋升为教授，2001年起先后担任浙江大学统计学研究所副所长、常务副所长、所长，浙江大学数学系副主任、数学科学学院副经理。现任浙江大学数据科学研究中心副主任、中国现场统计研究会常务理事、浙江省现场统计研究会理事长。主要从事临床试验自适应随机化设计、概率极限理论、相依数据模型等领域的研究，发表了学术论文170余篇，先后主持国家自然科学基金面上项目5项、杰出青年基金项目1项、重点项目1项，于2008年入选教育部“新世纪优秀人才支持计划”，2018年入选浙江省科技创新领军人才，2020年当选Institute of Mathematical Statistics Fellow。
报告题目：磁共振成像智能下采样与图像重建
报 告 人：庞彦伟
工作单位：天津大学
报告时间：2023-08-08 15:00-18:00
报告地点：bat365在线平台网站3401
报告摘要：
磁共振成像在人类生命健康观测领域发挥了巨大作用。但磁共振扫描速度慢，严重限制了成像设备的吞吐量、造成了患者预约时间过长的现象、增大了因患者运动导致成像失败的概率。本报告以下采样扫描提高磁共振成像效率为目的，汇报基于深度强化学习的自适应下采样扫描方法，在物理可实现的时间内智能地选择下一时刻扫描相位；介绍面向下采样数据的深度学习图像重建方法，包括单线圈重建、多线圈重建、三维重建和跨模态重建等。
报告人简介：
天津大学讲席教授、二级教授、天津市类脑智能技术重点实验室主任。国家万人计划科技创新领军人才、教育部青年长江学者。主持科技创新2030-新一代人工智能重大项目，主持国家自然科学基金国家重大科研仪器研制项目、重点项目、优青项目。获天津市科技进步一等奖、中国电子学会自然科学一等奖。连年入选Elsevier中国高被引学者。主要研究磁共振成像技术及仪器、视觉感知与类脑计算技术。
