Conference: Synergies between Nonparametrics, Sequential Analysis and Modern Data Science

会议：非参数学、序列分析和现代数据科学之间的协同作用

• 批准号: 2327589
• 负责人: Robert Keener
• 金额: $ 1.5万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2327589&HistoricalAwards=false
• 关键词: Conference; Synergies; between; Nonparametrics; Sequential

The Department of Statistics at the University of Michigan will host the conference titled “Synergies between Nonparametrics, Sequential Analysis and Modern Data Science” on the Ann Arbor campus from September 29 to 30, 2023. The conference will feature non-parallel sessions with talks on current research in statistics and probability by distinguished speakers. There will also be a poster session to give PhD students, postdocs, and junior professors an opportunity to present and receive feedback on their research. Beyond the educational value from the presentations, the conference should serve to foster collaboration and discussion among the speakers, faculty, and students participating in the event. Most of the funds from the NSF award will be used to support student participation in the conference, especially travel funds for non-local students.Planned session topics for the conference include: sequential analysis to reinforcement learning; shape constraints and beyond; limit theorems for dependent data; modern data science; nonparametrics and selection biases; and astrostatistics in the 21st century. For more information or to register to participate, please see the conference web-page: https://sites.lsa.umich.edu/woodroofememorial/This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

密歇根大学统计系将于2023年9月29日至30日在安阿伯校园举办题为“非参数化，顺序分析和现代数据科学之间的协同作用”的会议。 会议将以非平行会议为特色，由杰出的演讲者就统计和概率的当前研究进行演讲。 还将有一个海报会议，让博士生，博士后和初级教授有机会介绍和接受他们的研究反馈。 除了演讲的教育价值外，会议还应促进演讲者、教师和学生之间的合作和讨论。 本次会议的主题包括：强化学习的序贯分析;形状约束及超越;相关数据的极限定理;现代数据科学;非参数化和选择偏差;以及21世纪的天体统计学。 欲了解更多信息或注册参加，请参阅会议网页：https://sites.lsa.umich.edu/woodroofememorial/This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。