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Workshop on Applications-Driven Geometric Functional Data Analysis

Workshop on Applications-Driven Geometric Functional Data Analysis
应用驱动的几何函数数据分析研讨会
批准号:
1710802
负责人:
Anuj Srivastava
金额:
$2.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-07-01 至 2018-06-30

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中文摘要
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英文摘要
This award supports participation in a three-day workshop on applications-driven geometric functional data analysis (FDA) held October 8-10, 2017 on the campus of Florida State University in Tallahassee, Florida. The workshop focuses on topics in the intersections of FDA, infinite-dimensional differential geometry, and data-driven applications, and will feature both senior experts and junior researchers from these areas. The workshop includes a half-day of tutorials providing an introduction to the workshop topics, especially aimed at junior researchers. The remaining time will be allocated to invited talks, a poster session, and discussion sessions. The main motivation for this workshop is to initiate and facilitate discussions and future collaborations between US scientists and mathematicians with different backgrounds and expertise. The organizers will strive for breadth and diversity by targeting leading experts in the three components areas of the workshop -- geometry, FDA, and big data analysis. The poster session will be used to encourage all participants, especially the junior researchers, to present their research and interact with others. A rapid growth of functional data in all disciplines, ranging from natural and social sciences to engineering and technology, has made FDA an important topic of research. To handle the diverse challenges facing FDA, there is a need to exploit low-dimensional patterns and structures present in functional data. Geometry provides tools to: (1) extract and analyze structures in functional data, (2) handle the infinite-dimensionality of function spaces, (3) arrive at viable statistical models and make efficient inferences; and (4) process large datasets associated with many current and future data-centric applications. The workshop will include both: (1) theoretical topics, such as geometries of infinite-dimensional spaces, analysis under invariant metrics, and statistical models involving functional data; and (2) applications, such as computational anatomy, bioinformatics, biometrics, and neuroscience. This blend of important and complementary topics makes the workshop a unique and worthwhile event. For more information about the workshop, please refer to https://ani.stat.fsu.edu/GFDW/
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